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  • 1
    ISBN: 9783031460920
    Sprache: Englisch
    Seiten: 1 Online-Ressource(XXVI, 451 p. 178 illus., 165 illus. in color.)
    Ausgabe: 1st ed. 2023.
    Serie: Intelligent Systems Reference Library 247
    Paralleltitel: Erscheint auch als
    Paralleltitel: Erscheint auch als
    Paralleltitel: Erscheint auch als
    Schlagwort(e): Engineering ; Computational intelligence. ; Big data.
    Kurzfassung: Data Analytics For Smart Grids And Applications - Present And Future Directions -- Design, Optimization and Performance Analysis of Microgrids using Multi-Agent Q-Learning -- Big Data Analytics for Smart Grid: A Review on State-of- Art Techniques and Future Directions -- Smart Grid Management for Smart City Infrastructure using Wearable Sensors -- Studies on Conventional and Advanced Machine Learning Algorithm towards Framing of Robust Data analytics for the Smart Grid Application -- Prediction and Classification For Smart Grid Applications -- A Review on Smart Metering Using Artificial Intelligence and Machine Learning Techniques: Challenges and Solutions.
    Kurzfassung: This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    Online-Ressource
    Online-Ressource
    Basel : MDPI - Multidisciplinary Digital Publishing Institute
    ISBN: 9783036560830 , 9783036560847
    Sprache: Unbestimmte Sprache
    Seiten: 1 Online-Ressource (382 p.)
    Schlagwort(e): Technology: general issues ; History of engineering & technology ; Environmental science, engineering & technology
    Kurzfassung: The reprint focuses on artificial intelligence-based learning approaches and their applications in remote sensing fields. The explosive development of machine learning, deep learning approaches and its wide applications in signal processing have been witnessed in remote sensing. The new developments in remote sensing have led to a high resolution monitoring of ground on a global scale, giving a huge amount of ground observation data. Thus, artificial intelligence-based deep learning approaches and its applied signal processing are required for remote sensing. These approaches can be universal or specific tools of artificial intelligence, including well known neural networks, regression methods, decision trees, etc. It is worth compiling the various cutting-edge techniques and reporting on their promising applications
    Anmerkung: English
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    Basel : MDPI - Multidisciplinary Digital Publishing Institute
    ISBN: 9783036579467 , 9783036579474
    Sprache: Unbestimmte Sprache
    Seiten: 1 Online-Ressource (362 p.)
    Schlagwort(e): Research & information: general ; Geography
    Kurzfassung: This reprint provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology
    Anmerkung: English
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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