{"product_id":"artificial-intelligence-for-renewable-energy-systems-9781119761693","title":"Artificial Intelligence for Renewable Energy Systems","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book applies machine learning and deep learning techniques to model, forecast, and optimize renewable energy systems for efficient design. It covers topics such as algorithm selection, data forecasting, SCADA systems, intelligent condition monitoring, real-time decision-making, and energy consumption prediction in green buildings. The primary target audience includes research scholars, industry engineers, and graduate students. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 272 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 04 March 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: John Wiley \u0026amp; Sons Inc\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eRenewable energy systems, encompassing a wide range of options such as solar, wind, biodiesel, hybrid energy, and more, offer significant advantages over their conventional counterparts. This comprehensive book delves into the application of machine learning and deep learning techniques to model, forecast, and optimize renewable energy systems for efficient design. With the growing significance of renewable energy in today's world, this book aims to enhance the readers' understanding by covering current developments in the field. It explores topics such as the selection and application of machine learning algorithms for renewable energy systems, forecasting wind and solar radiation, intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA), intelligent condition monitoring of solar and wind energy systems, and an AI-based system for real-time decision-making in renewable energy systems. Furthermore, the chapter authors present experimental and real datasets with immense potential in the renewable energy sector, employing ML and DL algorithms to facilitate economic and environmental forecasting in the industry.\u003cbr\u003e\u003cbr\u003eThe primary target audience for this book includes research scholars, industry engineers, and graduate students specializing in renewable energy, electrical engineering, machine learning, and information \u0026amp; communication technology. By presenting cutting-edge research and practical applications, this book serves as a valuable resource for advancing the field of renewable energy systems and their optimization.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 467g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 229 x 152 x 16 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781119761693\u003c\/p\u003e","brand":"Vyas","offers":[{"title":"Hardback","offer_id":44106044702970,"sku":"9781119761693","price":156.42,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1676027312859_book.jpg?v=1676462585","url":"https:\/\/shulphink.com\/products\/artificial-intelligence-for-renewable-energy-systems-9781119761693","provider":"Shulph Ink","version":"1.0","type":"link"}