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  • 1
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    Online Resource
    12th World Conference “Intelligent System for Industrial Automation” (WCIS-2022) : Volume 1 (2024)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031515217
    Language: English
    Pages: 1 Online-Ressource(XV, 402 p. 118 illus., 67 illus. in color.)
    Edition: 1st ed. 2024.
    Series Statement: Lecture Notes in Networks and Systems 718
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Industrial engineering. ; Production engineering.
    Abstract: This book presents the first volume of the proceedings of the 12th World Conference "Intelligent systems for industrial automation", WCIS-2022 held in Tashkent, Uzbekistan, on November 25-26, 2022. It includes contributions from diverse areas of intelligent industrial systems design, intelligent information systems, decision making under imperfect information and others. The topics of the papers include hybrid control systems, pattern recognition, industry 4.0, information security, neural computing, fuzzy computation, decision making and support systems, and others.
    DOI: 10.1007/978-3-031-51521-7
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  • 2
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    New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms (2024)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031537134
    Language: English
    Pages: 1 Online-Ressource(X, 210 p. 73 illus., 61 illus. in color.)
    Edition: 1st ed. 2024.
    Series Statement: Studies in Computational Intelligence 1146
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: Towards Interval Type-3 Fuzzy Parameter Adaptation in Metaheuristics -- An Application of Controlled Sets in Medical Diagnosis -- Dynamic Adjustment of an Artificial Fish Swarm Algorithm using Shadowed Type-2 Fuzzy Logic for Enhancing Benchmark Function Optimization -- α-Interval Valued Fuzzy Sets and α-Interval Valued Fuzzy Subgroups -- Design of a Fuzzy PID controller for the balancing problem of a Quadruped Robot.
    Abstract: This book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. In this book, new directions on the theoretical developments of fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are offered. In addition, the abovementioned methods are discussed in application areas such as control and robotics, pattern recognition, medical diagnosis, decision-making, prediction and optimization of complex problems. There are a group of papers with the main theme of type-1, type-2 and type-3 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There is also a set of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of hybrid intelligent systems in real problems. There are also some papers that present theory and practice of neural networks in different applications. Finally, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas.
    DOI: 10.1007/978-3-031-53713-4
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  • 3
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    Type-3 Fuzzy Logic in Time Series Prediction (2024)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031597145
    Language: English
    Pages: 1 Online-Ressource(VIII, 99 p. 73 illus., 67 illus. in color.)
    Edition: 1st ed. 2024.
    Series Statement: SpringerBriefs in Computational Intelligence
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Engineering mathematics.
    Abstract: Chapter1. Type-3 Fuzzy Prediction -- Chapter 2. Type-3 for Prediction -- Chapter 3. Type-3 Fuzzy Logic in Time Series Prediction -- Chapter 4. Prediction with a Hybrid Interval Type-3 Fuzzy-Fractal Approach -- Chapter 5. Type-3 Fuzzy Aggregation of Neural Networks.
    Abstract: This book focuses on the field of type-3 fuzzy logic for applications in time series prediction. The main idea is that a higher type and order of fuzzy logic can help in solving various prediction problems and find better results. In addition, neural networks and fractal theory are employed in enhancing prediction results. In this regard, several hybrid intelligent methods are offered. In this book we test the proposed methods using several prediction problems, like predicting COVID-19 and the stock market. We can notice that when Type-3 fuzzy systems are implemented to model the behavior of systems, the results in prediction are enhanced, because the management of uncertainty is better. For this reason, we consider in this book the proposed methods using type-3 fuzzy systems, neural networks and fractal theory to improve the prediction behavior of the complex nonlinear systems. This book is intended to be a reference for scientists and engineers interested in applying type-3 fuzzy logic techniques for solving complex prediction problems. This book can also be used as a reference for graduate courses like the following: soft computing, fuzzy logic, neural networks, bio-inspired algorithms, intelligent prediction, and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.
    DOI: 10.1007/978-3-031-59714-5
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  • 4
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    12th World Conference “Intelligent System for Industrial Automation” (WCIS-2022) : Volume 2 (2024)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031534881
    Language: English
    Pages: 1 Online-Ressource(XV, 374 p. 143 illus., 93 illus. in color.)
    Edition: 1st ed. 2024.
    Series Statement: Lecture Notes in Networks and Systems 912
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Industrial engineering. ; Production engineering.
    Abstract: This book presents the proceedings of the 12th World Conference "Intelligent systems for industrial automation", WCIS-2022 held in Tashkent, Uzbekistan, on November 25-26, 2022. It includes contributions from diverse areas of intelligent industrial systems design, intelligent information systems, decision making under imperfect information and others. The topics of the papers include hybrid control systems, pattern recognition, industry 4.0, information security, neural computing, fuzzy computation, decision making and support systems, and others.
    DOI: 10.1007/978-3-031-53488-1
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  • 5
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    New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics (2024)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031556845
    Language: English
    Pages: 1 Online-Ressource(XII, 434 p. 153 illus., 114 illus. in color.)
    Edition: 1st ed. 2024.
    Series Statement: Studies in Computational Intelligence 1149
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: This book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. In this book, new horizons on the theoretical developments of fuzzy logic, neural networks and optimization algorithms are envisioned. In addition, the abovementioned methods are discussed in application areas such as control and robotics, pattern recognition, medical diagnosis, decision-making, prediction and optimization of complex problems. There are a group of papers with the main theme of type-1, type-2 and type-3 fuzzy systems, which basically consists of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There is also a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of hybrid intelligent systems in real problems. There are also a group papers that present theory and practice of neural networks in different applications. Finally, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas.
    DOI: 10.1007/978-3-031-55684-5
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  • 6
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    Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems (2023)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031320958
    Language: English
    Pages: 1 Online-Ressource(VIII, 232 p. 70 illus., 51 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Computational Intelligence 1100
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: Categories of Response-Based, Feature-Based, and Relation-Based Knowledge Distillation -- A Geometric Perspective on Feature-Based Distillation -- Knowledge Distillation Across Vision and Language -- Knowledge Distillation in Granular Fuzzy Models by Solving Fuzzy Relation Equations -- Ensemble Knowledge Distillation for Edge Intelligence in Medical Applications -- Self-Distillation with the New Paradigm in Multi-Task Learning -- Knowledge Distillation for Autonomous Intelligent Unmanned System.
    Abstract: The book provides a timely coverage of the paradigm of knowledge distillation—an efficient way of model compression. Knowledge distillation is positioned in a general setting of transfer learning, which effectively learns a lightweight student model from a large teacher model. The book covers a variety of training schemes, teacher–student architectures, and distillation algorithms. The book covers a wealth of topics including recent developments in vision and language learning, relational architectures, multi-task learning, and representative applications to image processing, computer vision, edge intelligence, and autonomous systems. The book is of relevance to a broad audience including researchers and practitioners active in the area of machine learning and pursuing fundamental and applied research in the area of advanced learning paradigms.
    DOI: 10.1007/978-3-031-32095-8
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  • 7
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    Recent Trends on Type-2 Fuzzy Logic Systems: Theory, Methodology and Applications (2023)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031263323
    Language: English
    Pages: 1 Online-Ressource(XII, 265 p. 140 illus., 114 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Fuzziness and Soft Computing 425
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: Chapter 1: Application of interval type-2 fuzzy logic control approach to the lower-limb exoskeleton -- Chapter 2: A Simplified Model of an Interval Type-2 Takagi-Sugeno Fuzzy PID Controller using 1- D Input Space -- Chapter 3: Fractional order Type-2 fuzzy Logic controllers -- Chapter 4: Artificial Bee Colony Optimized a new Precompensated Interval Type-2 Fuzzy Logic Controller for a Magnetic Levitation System -- Chapter 5: Application of Type-2 Fuzzy Logic Controllers in Renewable Energy Systems. .
    Abstract: This book covers the introduction, theory, development and applications of type-2 fuzzy logic systems, which represent the current state-of-the-art in various domains such as control applications, power plants, health care, image processing, mathematical applications etc. The book is also rich in discussing different applications in order to give the researchers a flavor of how type-2 fuzzy logic is designed for different types of problems. Type-2 fuzzy logic systems are now used extensively in engineering applications for many purposes. In simple language, this book covers the practical use of type-2 fuzzy logic and its optimization through different training methods. Furthermore, this book maintains the relationship between mathematics and practical implementations in the real world. This book chapter also contains the proper comparisons with available literature work. It shows that the presented enhanced techniques have better results. This book would serve as a handy reference guide for a variety of readers, primarily targeting research scholars, undergraduate and postgraduate researchers and practicing engineers working in Type-2 fuzzy logic systems and their applications. .
    DOI: 10.1007/978-3-031-26332-3
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  • 8
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    Preferential Voting and Applications: Approaches Based on Data Envelopment Analysis (2023)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031304033
    Language: English
    Pages: 1 Online-Ressource(IX, 185 p. 34 illus., 9 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Systems, Decision and Control 471
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Operations research.
    Abstract: Basic concepts of voting -- Preferential voting based on data envelopment analysis -- Group preferential voting -- Applications of preferential voting in industry and society.
    Abstract: This book presents the theory and application of the models presented in this regard and establishes a meaningful relationship between data envelopment analysis and multi-attribute decision making. The issue of "choice" using the aggregation of voters' votes is one of the most important group decision-making issues that are always considered by decision makers in electoral systems. Voting is a method of group decision making in a democratic society that expresses the will of the majority. Voting is perhaps the simplest way to gather the opinions of experts, and this ease of application has made it a multi-attribute decision-making method in group decisions. Preferential voting is a type of voting that may refer to electoral systems or groups of the electoral system. In preferential voting, voters vote for multiple candidates, and how the candidates are arranged on the ballot is important. Researchers have made many efforts to provide models of voter aggregation, and one of the best results of these efforts is the aggregation of votes based on the policy of data envelopment analysis. Thus, in group decisions, the opinions of experts are obtained in a simple structure and consolidated in an interactive and logical structure, and the results can be a powerful tool for decision support. This book provides a complete set of voting models based on data envelopment analysis and expressing its various applications in industry and society. However, most decision-making methods do not use the opinions of experts or reduce the motivation of experts to participate in complex interactions and time, while voting methods do not have this shortcoming. This book is suitable for graduate students in the fields of industrial management, business management, industrial engineering, applied mathematics, and economics. It can also be a good source for researchers in decision science, decision support systems, data envelopment analysis, supply chain management, healthcare management, and others. The methods presented in this book can not only offer a comprehensive framework for solving the problems of these areas but also can inspire researchers to pursue new innovative hybrid methods.
    DOI: 10.1007/978-3-031-30403-3
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  • 9
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    Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics (2023)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031289996
    Language: English
    Pages: 1 Online-Ressource(XII, 498 p. 251 illus., 187 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Computational Intelligence 1096
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: A decision-making approach based on multiple neural networks for clustering and prediction of time series -- Approximation of Physicochemical Properties based on a Mes-sage Passing Neural Network Approach -- Quanvolutional Neural Network applied to MNIST -- Traffic Sign Recognition Using Fuzzy Preprocessing and Deep Neural Networks -- Fuzzy dynamic adaptation of an Artificial Fish Swarm Algo-rithm for the Optimization of Benchmark Functions -- Particle Swarm Optimization Algorithm with Improved Opposi-tion-Based Learning (IOBL-PSO) to Solve Continuous Problems -- Study on the effect of chaotic maps in the formation of new uni-verses in the Multiverse Optimizer algorithm -- Performance comparative of surrogate models as fitness func-tions for metaheuristic algorithms -- A New Continuous Mycorrhiza Optimization Nature-Inspired Algorithm -- Optimal Tuning of an Active Disturbance Rejection Controller using a Particle Swarm Optimization algorithm -- Optimization of Fuzzy Controllers using Distributed Bioinspired Methods with Random parameters -- Application of Compensatory Fuzzy Logic in Diabetes Problem Using Pima-Indians Dataset -- Comparison of the effect of parameter adaptation in bio-inspired CS algorithm using Type-2 Fuzzy Logic -- Interpretability of an Archimedean Compensatory Fuzzy Logic in Data Analytics: some case studies -- A new selection and class prediction using type-1 fuzzy logic ap-plied to a convolutional neural network -- Relaxed Differential Evolution Algorithm -- Automatic Characterization of Time Series Using Metaheuristic Algorithms for Epidemics Spread Analysis -- Comparative study of heuristics for the One-dimensional Bin Pa-cking Problem -- Experimental Evaluation of Adaptive Operators Selection Methods for the Dynamic Multiobjective Evolutionary Algorithm Based on Decomposition (DMOEA/D) -- Automated Machine Learning to improve stock-market forecast-ing using PSO and LSTM networks -- Evolutionary Gaussian-Gradient: A new optimization algorithm for the electromechanical design of gravitational batteries -- A comparison between selection operators heuristics of perturba-tion in CSP -- Trajectory Tracking Control of Wheeled Mobile Robots Using Neural Networks and Feedback Control Techniques -- An Evolutionary Bilevel Optimization Approach for Neuroevolu-tion -- Recovering from population extinction in the Animal Life Cycle Algorithm (ALCA) -- Multi-objective optimization through coevolution and outranking methods with uncertainty management -- EDA Experimental Proposal with Mallows Distribution applied to the Mixed No-idle Permutation Flowshop Scheduling problem -- Interval Type-3 Fuzzy Decision Making in Material Surface Quality Control -- Interval Type-3 Fuzzy Decision Making in Quality Evaluation for Speaker Manufacturing.
    Abstract: In this book, recent theoretical developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are presented in application areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are a group of papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different application areas. In addition, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas. Finally, there are a group of papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.
    DOI: 10.1007/978-3-031-28999-6
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  • 10
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    Comparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis (2023)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031431814
    Language: English
    Pages: 1 Online-Ressource(XIV, 180 p. 32 illus., 29 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Big Data 138
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Engineering ; Computational intelligence. ; Big data.
    Abstract: Relationship between DEA models without explicit inputs and DEA-R models -- Finding efficient surfaces in DEA-R models -- Cost and revenue efficiency in DEA-R models -- A Novel Slack-Based Model for Efficiency and Super-efficiency in DEA-R -- A Multi-Criteria Ratio-Based Approach for Two-Stage Data Envelopment Analysis -- A novel network DEA-R model for evaluating hospital services supply chain performance -- A novel inverse DEA-R model for inputs/output estimation -- Evaluation of Two-Stage Networks based on Average Efficiency Using DEA and DEA-R with Fuzzy Data -- Stochastic network DEA-R models for two-stage systems.
    Abstract: The combination of DEA and ratio analysis is introduced as a suitable field for evaluating the performance of DMUs. In this regard, DEA-R is also proposed as a hybrid technique for calculating efficiency, ranking DMUs, and finding efficient faces. Therefore, the relationship between DEA and DEA-R provides a suitable field for researchers in the field of evaluating the performance of DMUs. The audience of this book is not limited to researchers in mathematics fields, but experts and students in industrial engineering and management fields also benefit from the topics of this book.
    DOI: 10.1007/978-3-031-43181-4
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  • 11
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    Fuzzy Decision Analysis: Multi Attribute Decision Making Approach (2023)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031447426
    Language: English
    Pages: 1 Online-Ressource(XXII, 344 p. 32 illus., 16 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Computational Intelligence 1121
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Operations research.
    Abstract: Foundations of Decision -- Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS) in uncertainty environment -- The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) in uncertainty environment -- The Multi-Objective Optimization Ratio Analysis (MOORA) in uncertainty environment.
    Abstract: Authored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.
    DOI: 10.1007/978-3-031-44742-6
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  • 12
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    Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design (2023)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031220425
    Language: English
    Pages: 1 Online-Ressource(X, 252 p. 82 illus., 52 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Computational Intelligence 1061
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: On Decision Making Applications Via Distance Measures -- On Intuitionistic Fuzzy Abstract Algebras -- Generalization of Intuitionistic Fuzzy Submodules of a Module by using Triangular Norms and Conorms and (T, S)-L Subrings -- Fuzzy Dynamic Parameter Adaptation in the Mayfly Algorithm: Implementation of fuzzy adaptation and tests on benchmark functions and Mackey Glass neural network -- Fuzzy classifier using the optimization algorithm by means of particles for the diagnosis of arterial hypertension -- A Survey of Models and Solution Methods for the Internet Shopping Optimization Problem -- A comparison between MFCC and MSE features for text-independent speaker recognition using machine learning algorithms -- Forecasting based on Fuzzy Logic of the Level of Epidemiological Risk for the Mexican State of Tamaulipas -- Bio-Inspired Flower Pollination Algorithm for the Optimization of a Monolithic Neural Network -- Rendezvous and Docking Control of Satellites Using Chaos Synchronization Method with Intuitionistic Fuzzy Sliding Mode Control -- Optimizing a convolutional neural network with a hierarchical genetic algorithm for diabetic retinopathy detection -- Interval Type-3 Fuzzy Systems: a natural evolution from type-1 and type-2 fuzzy systems -- A comparative study between bird swarm algorithm and artificial gorilla troops optimize -- Particle Swarm Optimization of Convolutional Neural Networks for Diabetic Retinopathy Classification.
    Abstract: This book covers recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations. In addition, the above-mentioned methods are applied to areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Nowadays, the main topic of the book is highly relevant, as most current intelligent systems and devices in use utilize some form of intelligent feature to enhance their performance. In addition, on the theoretical side, new and advanced models and algorithms of type-2 and type-3 fuzzy logic are presented, which are of great interest to researchers working on these areas. Also, new nature-inspired optimization algorithms and innovative neural models are put forward in the manuscript, which are very popular subjects, at this moment. There are contributions on theoretical aspects as well as applications, which make the book very appealing to a wide audience, ranging from researchers to professors and graduate students.
    DOI: 10.1007/978-3-031-22042-5
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  • 13
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    Type-3 Fuzzy Logic in Intelligent Control (2023)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031460883
    Language: English
    Pages: 1 Online-Ressource(VIII, 85 p. 58 illus., 54 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: SpringerBriefs in Computational Intelligence
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Engineering mathematics.
    Abstract: Type-3 Fuzzy Control -- Type-3 Fuzzy Theory -- Review of Type-3 Fuzzy Control -- Approach for Type-3 Fuzzy Control -- Fuzzy Differential Evolution for Optimal Fuzzy Controller Parameterization -- Interval Type-3 Fuzzy Parameter Adaptation in Harmony Search Optimal Controller Design -- Conclusion of Interval Type-3 Fuzzy Control.
    Abstract: This book focuses on the field of type-3 fuzzy logic, also considering metaheuristics for applications in the control area. The main idea is that these areas together can solve various control problems and find better results. In this book, we test the proposed method using several benchmark problems, such as the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. We notice that when interval type-3 fuzzy systems are implemented to model the behavior of the systems, the results in control show a better stabilization, because the management of uncertainty is better. For this reason, we consider in this book the proposed method using type-3 fuzzy systems, fuzzy controllers, and metaheuristic algorithms to improve the control behavior of complex nonlinear plants. This book is intended to be a reference for scientists and engineers interested in applying type-3 fuzzy logic techniques for solving problems in intelligent control. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.
    DOI: 10.1007/978-3-031-46088-3
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  • 14
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    Artificial Intelligence in Control and Decision-making Systems : Dedicated to Professor Janusz Kacprzyk (2023)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031257599
    Language: English
    Pages: 1 Online-Ressource(XVIII, 388 p. 118 illus., 56 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Computational Intelligence 1087
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Control engineering. ; Artificial intelligence.
    Abstract: Method for the Computation of the Interval Hull to Solutions of Interval and Fuzzy Interval Linear Systems -- Fuzzy-Petri-Networks in Supervisory Control of Markov Processes in Robotized FMS and Robotic Systems -- Using Fuzzy Set Approaches for Linguistic Data Summaries -- Fuzzy or Neural, Type-1 or Type-2 – When Each Is Better: First-Approximation Analysis.
    Abstract: This book presents an authoritative collection of contributions reporting on computational intelligence, fuzzy systems as well as artificial intelligence techniques for modeling, optimization, control and decision-making together with applications and case studies in engineering, management and economic sciences. Dedicated to the Academician of the Polish Academy of Sciences, Professor Janusz Kacprzyk in recognition of his pioneering work, the book reports on theories, methods and new challenges in artificial intelligence, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike. The book consists of the 18 chapters, presented by distinguished and experienced authors from 16 different countries (Australia, Brazil, Canada, Chile, Germany, Hungary, Israel, Italy, China, R.N.Macedonia, Saudi Arabia, Spain, Turkey, United States, Ukraine, and Vietnam). All chapters are grouped into three parts: Computational Intelligence and Fuzzy Systems, Artificial Intelligence Techniques in Modelling and Optimization, and Computational Intelligence in Control and Decision Support Processes. The book reflects recent developments and new directions in artificial intelligence, including computation method of the interval hull to solutions of interval and fuzzy interval linear systems, fuzzy-Petri-networks in supervisory control of Markov processes in robotic systems, fuzzy approaches for linguistic data summaries, first-approximation analysis for choosing fuzzy or neural systems and type-1 or type-2 fuzzy sets, matrix resolving functions in game dynamic problems, evolving stacking neuro-fuzzy probabilistic networks and their combined learning in online pattern recognition tasks, structural optimization of fuzzy control and decision-making systems, neural and granular fuzzy adaptive modeling, state and action abstraction for search and reinforcement learning algorithms. Among the most successful and perspective implementations in practical areas of human activity are tentative algorithms for neurological disorders, human-centric question-answering system, OWA operators in pensions, evaluation of the perception of public safety through fuzzy and multi-criteria approach, a multicriteria hierarchical approach to investment location choice, intelligent traffic signal control and generative adversarial networks in cybersecurity.
    DOI: 10.1007/978-3-031-25759-9
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  • 15
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    Mycorrhiza Optimization Algorithm (2023)
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    Details
    ISBN: 9783031473692
    Language: English
    Pages: 1 Online-Ressource(VIII, 78 p. 32 illus., 26 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: SpringerBriefs in Computational Intelligence
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Engineering mathematics.
    Abstract: Introduction to the Mycorrhiza Optimization Algorithm -- Theory for the Mycorrhiza Optimization Algorithm -- Background for the Mycorrhiza Algorithm -- Problem Definition -- CMOA – Continuous Mycorrhiza Optimization Algorithm -- DMOA – Discrete Mycorrhiza Optimization Algorithm -- Conclusions of the Mycorrhiza Optimization Algorithm.
    Abstract: This book provides two new optimization algorithms to address real optimization problems. Optimization is a fundamental concept in engineering and science, and its applications are needed in many fields. From designing products and systems to developing algorithms and models, optimization plays a critical role in achieving efficient and effective solutions to complex problems. Optimization algorithms inspired by nature have proven effective in solving a wide range of problems, including those in engineering, finance, and machine learning. These algorithms are often used when traditional optimization techniques are impractical due to the size or complexity of the problem. In this book, we are presenting two new optimization algorithms inspired by plant roots and the Mycorrhiza Network. The first algorithm is called the Continuous Mycorrhiza Optimization Algorithm (CMOA), which was proposed based on the model of the Continuous Lotka-Volterra System Equations. The second algorithm is called the Discrete Mycorrhiza Optimization Algorithm (DMOA), which design based on the model of Discrete Lotka-Volterra System Equations. By mastering the proposed algorithms, the readers able to develop innovative solutions that improve efficiency, reduce costs, and improve performance in the corresponding field of work.
    DOI: 10.1007/978-3-031-47369-2
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  • 16
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    Modern Adaptive Fuzzy Control Systems (2023)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031173936
    Language: English
    Pages: 1 Online-Ressource(X, 157 p. 95 illus., 91 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Fuzziness and Soft Computing 421
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Control engineering. ; Artificial intelligence.
    Abstract: Chapter 1: An Introduction to Fuzzy and Fuzzy Control Systems -- Chapter 2: Classification of Adaptive Fuzzy Controllers -- Chapter 3: Type-2 Fuzzy Systems -- Chapter 4: Training Interval Type-2 Fuzzy Systems Based on Error Backpropagation.
    Abstract: This book explains the basic concepts, theory and applications of fuzzy systems in control in a simple unified approach with clear ex-amples and simulations in the MATLAB programming language. Fuzzy systems, especially, type-2 neuro-fuzzy systems, are now used extensively in various engineering fields for different purposes. In plain language, this book aims to practically explain fuzzy sys-tems and different methods of training and optimizing these systems. For this purpose, type-2 neuro-fuzzy systems are first analyzed along with various methods of training and optimizing these systems through implementation in MATLAB. These systems are then em-ployed to design adaptive fuzzy controllers. The authors aim at pre-senting all the well-known optimization methods clearly and code them in the MATLAB language.
    DOI: 10.1007/978-3-031-17393-6
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  • 17
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    Recent Advancements in Multi-View Data Analytics (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783030952396
    Language: English
    Pages: 1 Online-Ressource(VIII, 342 p. 74 illus., 47 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Studies in Big Data 106
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Engineering—Data processing. ; Computational intelligence. ; Artificial intelligence.
    Abstract: The Psychology of Conflictive Uncertainty -- How Multi-View Techniques Can Help in Processing Uncertainty -- Multi-View Clustering and Multi-View Models -- Rethinking Collaborative Clustering: A Practical and Theoretical Study within the Realm of Multi-View Clustering -- An Optimal Transport Framework for Collaborative Multi-View Clustering -- Data Anonymization through Multi-Modular Clustering.
    Abstract: This book provides timely studies on multi-view facets of data analytics by covering recent trends in processing and reasoning about data originating from an array of local sources. A multi-view nature of data analytics is encountered when working with a variety of real-world scenarios including clustering, consensus building in decision processes, computer vision, knowledge representation, big data, data streaming, among others. The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.
    DOI: 10.1007/978-3-030-95239-6
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  • 18
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    Interval Type-3 Fuzzy Systems: Theory and Design (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783030965150
    Language: English
    Pages: 1 Online-Ressource(VIII, 102 p. 60 illus., 46 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Studies in Fuzziness and Soft Computing 418
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: Chapter 1: Introduction to Interval Type-3 Fuzzy Systems -- Chapter 2: Type-2 Fuzzy Logic Systems -- Chapter 3: Interval Type-3 Fuzzy Sets -- Chapter 4: Interval Type-3 Fuzzy Logic Systems -- Chapter 5: Conclusions of Type-3 Fuzzy Systems.
    Abstract: This book briefly reviews the basic concepts of type-2 fuzzy systems and then describes the proposed definitions for interval type-3 fuzzy sets and relations, also interval type-3 inference and systems. The use of type-2 fuzzy systems has become widespread in the leading economy sectors, especially in industrial and application areas, such as services, health, defense, and so on. However, recently the use of interval type-3 fuzzy systems has been receiving increasing attention and some successful applications have been developed in the last year. These issues were taken into consideration for this book, as we did realize that there was a need to offer the main theoretical concepts of type-3 fuzzy logic, as well as methods to design, develop and implement the type-3 fuzzy systems. A review of basic concepts and their use in the design and implementation of interval type-3 fuzzy systems, which are relatively new models of uncertainty and imprecision, are presented. The main focus of this work is based on the basic reasons of the need for interval type-3 fuzzy systems in different areas of application. In addition, we describe methods for designing interval type-3 fuzzy systems and illustrate this with some examples and simulations.
    DOI: 10.1007/978-3-030-96515-0
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  • 19
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    Hybrid Intelligent Systems : 21st International Conference on Hybrid Intelligent Systems (HIS 2021), December 14–16, 2021 (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783030963057
    Language: English
    Pages: 1 Online-Ressource(XV, 669 p. 305 illus., 225 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Lecture Notes in Networks and Systems 420
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: YOLOv5 Based Deep Convolutional Neural Networks for Vehicle Recognition in Smart University Campus -- Analysis of Twitter User's Sentiment Against Covid-19 Vaccination Using the Lexicon Based Method -- Dual Connectivity Handoff Analysis for ENDC C/U-plane Split NSA NR5G Networks -- Blockchain Integrated Machine Learning For Training Autonomous Cars -- Privacy Preservation Technique based on Sensitivity Levels for Multiple Numerical Sensitive Overlapped Attributes -- Feature Ranking Based Carrot Disease Recognition Using MIFS Method -- Designing Knowledge-Based Systems for COVID-19 Diagnosis.
    Abstract: This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 45 selected papers from the 20th International Conference on Hybrid Intelligent Systems (HIS 2021) and 16 papers from the 17th International Conference on Information Assurance and Security, which was held online, from December 14 to 16, 2021. A premier conference in the field of artificial intelligence and machine learning applications, HIS-IAS 2021 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from over 20 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of computer science and engineering.
    DOI: 10.1007/978-3-030-96305-7
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  • 20
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    Contemporary Fuzzy Logic : A Perspective of Fuzzy Logic with Scilab (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783030989743
    Language: English
    Pages: 1 Online-Ressource(XI, 136 p. 63 illus., 40 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Big and Integrated Artificial Intelligence 1
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: Introduction to fuzzy sets -- Fuzzy numbers -- Fuzzy relations -- Fuzzy logic -- Fuzzy inference systems -- Combining artificial neural networks and fuzzy sets -- Fuzzy transform -- Introduction to granular computing.
    Abstract: This book offers an essential introduction to fuzzy logic, starting with the classical notions and going through more advanced notions from the current state-of-the-art research. Each of the major topics is accompanied by examples, problems and Scilab codes. As a free open source software, Scilab offers everyone the chance to practice the concepts learned through the book. The book represents a synthesis of authors’ research and experience through the lectures delivered to university students. It is primarily intended as a textbook for upper-level undergraduates and graduates in computer science, mathematics, physics and engineering. It also represents a valuable resource for practitioners and researchers alike, bringing ideas for projects in the broad field of fuzzy logic.
    DOI: 10.1007/978-3-030-98974-3
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  • 21
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    New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783031082665
    Language: English
    Pages: 1 Online-Ressource(XII, 483 p. 188 illus., 131 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Studies in Computational Intelligence 1050
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: Automated Medical Diagnosis & Classification of Skin Diseases Using Efficinetnet-B0 Convolutional Neural Network -- Modular Approach for Neural Networks in medical image classi-fication with enhanced fuzzy integration -- Clustering and prediction of time series for traffic accidents using a nested layered artificial neural network model.
    Abstract: In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems. .
    DOI: 10.1007/978-3-031-08266-5
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  • 22
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    A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783030822880
    Language: English
    Pages: 1 Online-Ressource(VIII, 71 p. 33 illus., 28 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: SpringerBriefs in Computational Intelligence
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Engineering mathematics. ; Elementary particles (Physics). ; Quantum field theory.
    Abstract: Introduction -- Literature Review -- String Theory Algorithm -- Simulation Results -- Conclusions.
    Abstract: This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.
    DOI: 10.1007/978-3-030-82288-0
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  • 23
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    11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021 (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783030921279
    Language: English
    Pages: 1 Online-Ressource(XVII, 785 p. 255 illus., 167 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Lecture Notes in Networks and Systems 362
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: This book presents the proceedings of the 11th Conference on Theory and Applications of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence, ICSCCW-2021, held in Antalya, Turkey, on August 23–24, 2021. The general scope of the book covers uncertain computation, decision making under imperfect information, neuro-fuzzy approaches, natural language processing, and other areas. The topics of the papers include theory and application of soft computing, computing with words, image processing with soft computing, intelligent control, machine learning, fuzzy logic in data mining, soft computing in business, economics, engineering, material sciences, biomedical engineering, and health care. This book is a useful guide for academics, practitioners, and graduates in fields of soft computing and computing with words. It allows for increasing of interest in development and applying of these paradigms in various real-life fields.
    DOI: 10.1007/978-3-030-92127-9
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  • 24
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    Soft Computing for Data Analytics, Classification Model, and Control (2022)
    Cham : Springer International Publishing | Cham : Imprint: Springer
    Details
    ISBN: 9783030920265
    Language: English
    Pages: 1 Online-Ressource(VIII, 165 p. 83 illus., 61 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Studies in Fuzziness and Soft Computing 413
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence—Data processing. ; Bioinformatics. ; Control engineering.
    Abstract: Chapter 1: An Optimization of Fuzzy Rough Set Nearest Neighbor Classification Model using Krill Herd Algorithm for Sentiment Text Analytics -- Chapter 2: Fuzzy Wavelet Neural Network with Social Spider Optimization Algorithm for Pattern Recognition in Medical Domain -- Chapter 3: Fuzzy with Gravitational Search Algorithm Tuned Radial Basis Function Network for Medical Disease Diagnosis and Classification Model -- Chapter 4: Optimal Neutrosophic Rules based Feature Extraction for Data Classification using Deep Learning Model -- Chapter 5: Self-Evolving Interval Type-2 Fuzzy Neural Network Design for The Synchronization of Chaotic Systems -- Chapter 6: Categorizing Relations via Semi-Supervised Learning using a Hybrid Tolerance Rough Sets and Genetic Algorithm Approach -- Chapter 7: Data-driven Fuzzy C-Means Equivalent Turbine-governor for Power System Frequency Response -- Chapter 8: Multicriteria group decision making using a novel similarity measure for triangular fuzzy numbers based on their newly defined expected values and variances -- Chapter 9: Bangla Printed Character Generation from Handwritten Character Using GAN.
    Abstract: This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control. The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design of hybrid algorithms for applications in data analytics, classification model, and engineering control.
    DOI: 10.1007/978-3-030-92026-5
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