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Название: Soft Computing Applications for Advancements in Power Systems
Автор: Vijay Kumar Sood, Krishna Murari, Om Hari Gupta, Anupam Kumar
Издательство: River Publishers
Год: 2024
Страниц: 293
Язык: английский
Формат: pdf (true)
Размер: 11.9 MB
This book discusses real applications of Soft Computing (SC) in power systems. These SC techniques, inspired by the human mind and biological behavior, have proven to be excellent tools to overcome the challenges faced in power systems and related areas. The techniques are robust and provide low-cost solutions while also offering an effective solution for studying and modeling the behavior of renewable energy generation, operation of grid-connected renewable energy systems, and sustainable decision-making among alternatives. Some important branches of soft computing techniques are neural networks, fuzzy logic, evolutionary computation, probabilistic reasoning, etc. A neural network can learn and adapt as per requirements. Fuzzy logic is based on an expert’s knowledge and evolutionary computation is established on Darwin’s principle of “survival of the fittest strategy” and genetic evolution. The Soft Computing techniques are highly robust, adaptable, and low cost. Furthermore, it is observed that soft computing techniques are also applicable in different fields such as robotics, aerospace, pattern classification and recognition, medical applications, market prediction, power system applications, etc.
Автор: Vijay Kumar Sood, Krishna Murari, Om Hari Gupta, Anupam Kumar
Издательство: River Publishers
Год: 2024
Страниц: 293
Язык: английский
Формат: pdf (true)
Размер: 11.9 MB
This book discusses real applications of Soft Computing (SC) in power systems. These SC techniques, inspired by the human mind and biological behavior, have proven to be excellent tools to overcome the challenges faced in power systems and related areas. The techniques are robust and provide low-cost solutions while also offering an effective solution for studying and modeling the behavior of renewable energy generation, operation of grid-connected renewable energy systems, and sustainable decision-making among alternatives. Some important branches of soft computing techniques are neural networks, fuzzy logic, evolutionary computation, probabilistic reasoning, etc. A neural network can learn and adapt as per requirements. Fuzzy logic is based on an expert’s knowledge and evolutionary computation is established on Darwin’s principle of “survival of the fittest strategy” and genetic evolution. The Soft Computing techniques are highly robust, adaptable, and low cost. Furthermore, it is observed that soft computing techniques are also applicable in different fields such as robotics, aerospace, pattern classification and recognition, medical applications, market prediction, power system applications, etc.