This book addresses the frontier advances in the theory and application of nature-inspired optimization techniques, including solving the quadratic assignment problem, prediction in nature-inspired dynamic optimization, the lion algorithm and its applications, optimizing the operation scheduling of microgrids, PID controllers for two-legged robots, optimizing crane operating times, planning electrical energy distribution systems, automatic design and evaluation of classification pipelines, and optimizing wind-energy power generation plants. The book also presents a variety of nature-inspired methods and illustrates methods of adapting these to said applications.
Nature-inspired computation, developed by mimicking natural phenomena, makes a significant contribution toward the solution of non-convex optimization problems that normal mathematical optimizers fail to solve. As such, a wide range of nature-inspired computing approaches has been used in multidisciplinary engineering applications. Written by researchers and developers from a variety of fields, this book presents the latest findings, novel techniques and pioneering applications.Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Nilesh Patel is an Associate Professor in the Department of Computer Science and Engineering at Oakland University, Rochester, Michigan. Prior to his tenure at Oakland University, he served as an Assistant Professor at the University of Michigan, Dearborn. In addition to his academic service, Dr. Patel served as a Software Architect and Software Engineering Manager at Ford Motors and Visteon Corporation, where he played an instrumental role in design and development of first voice-enabled vehicular control and GPS navigation systems. His research interests include deep machine learning, pattern recognition, visual computing, evolutionary computing, and big data analytics.
Tomonobu Senjyu (SM'06) was born in Saga Prefecture, Japan, in 1963. He received the B.S. and M.S. degrees in Electrical Engineering from the University of the Ryukyus, Nishihara, Japan, in 1986 and 1988,respectively, and the Ph.D. degree in Electrical Engineering from Nagoya University, Nagoya, Japan, in 1994. He is currently a Full Professor in the Department of Electrical and Electronics Engineering, University of the Ryukyus. His research interests are in the areas of renewable energy, power system optimization and operation, power electronics, and advanced control of electrical machines.
This book addresses the frontier advances in the theory and application of nature-inspired optimization techniques, including solving the quadratic assignment problem, prediction in nature-inspired dynamic optimization, the lion algorithm and its applications, optimizing the operation scheduling of microgrids, PID controllers for two-legged robots, optimizing crane operating times, planning electrical energy distribution systems, automatic design and evaluation of classification pipelines, and optimizing wind-energy power generation plants. The book also presents a variety of nature-inspired methods and illustrates methods of adapting these to said applications.
Nature-inspired computation, developed by mimicking natural phenomena, makes a significant contribution toward the solution of non-convex optimization problems that normal mathematical optimizers fail to solve. As such, a wide range of nature-inspired computing approaches has been used in multidisciplinary engineering applications. Written by researchers and developers from a variety of fields, this book presents the latest findings, novel techniques and pioneering applications.„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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