Description

Smart Grids as Cyber Physical Systems, a new two-volume set from Wiley-Scrivener, provides a comprehensive overview of the fundamental security of supervisory control and data acquisition (SCADA) systems, offering clarity on specific operating and security issues that may arise that deteriorate the overall operation and efficiency of smart grid systems. It also provides techniques to monitor and protect systems, as well as aids for designing a threat-free system. This title discusses how artificial intelligence (AI) may be extensively deployed in the prediction of energy generation, electric grid-related line loss prediction, load forecasting, and for predicting equipment failure prevention. It also discusses power generation systems, building service systems, and explores advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms. Additionally, we will explore research contribution of experts in CPS infrastructure systems

Smart Grids as Cyber Physical Systems 2 Volume Set

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£200.04

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Usually despatched within 5 days
Hardback by OVG Swathika

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Smart Grids as Cyber Physical Systems, a new two-volume set from Wiley-Scrivener, provides a comprehensive overview of the fundamental security... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 1/22/2024 12:07:00 AM
    ISBN13: 9781394261697, 978-1394261697
    ISBN10: 1394261691

    Non Fiction , Mathematics & Science , Education

    Description

    Smart Grids as Cyber Physical Systems, a new two-volume set from Wiley-Scrivener, provides a comprehensive overview of the fundamental security of supervisory control and data acquisition (SCADA) systems, offering clarity on specific operating and security issues that may arise that deteriorate the overall operation and efficiency of smart grid systems. It also provides techniques to monitor and protect systems, as well as aids for designing a threat-free system. This title discusses how artificial intelligence (AI) may be extensively deployed in the prediction of energy generation, electric grid-related line loss prediction, load forecasting, and for predicting equipment failure prevention. It also discusses power generation systems, building service systems, and explores advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms. Additionally, we will explore research contribution of experts in CPS infrastructure systems

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