This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems mainly discussing developments highlighting their modeling and simulation and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines drones and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems in the areas of artificial intelligence cryptography embedded hardware electronics the Internet of Things and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research. Features Provides details of applications using machine learning methods to solve real problems in engineering Discusses new developments in the areas of complex and unmanned systems Includes details of hardware/software implementation of machine learning methods Includes examples of applications of different machine learning methods for future lines for research in the hot topic areas of submarines drones robots cryptography electronics healthcare and the Internet of Things This book can be used by graduate students industrial and academic professionals to examine real case studies in applying machine learning in the areas of modeling simulation and optimization of complex systems cryptography electronics healthcare control systems Internet of Things security and unmanned systems such as submarines drones and robots. | Machine Learning for Complex and Unmanned Systems
This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems mainly discussing developments highlighting their modeling and simulation and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines drones and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems in the areas of artificial intelligence cryptography embedded hardware electronics the Internet of Things and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research. Features Provides details of applications using machine learning methods to solve real problems in engineering Discusses new developments in the areas of complex and unmanned systems Includes details of hardware/software implementation of machine learning methods Includes examples of applications of different machine learning methods for future lines for research in the hot topic areas of submarines drones robots cryptography electronics healthcare and the Internet of Things This book can be used by graduate students industrial and academic professionals to examine real case studies in applying machine learning in the areas of modeling simulation and optimization of complex systems cryptography electronics healthcare control systems Internet of Things security and unmanned systems such as submarines drones and robots. | Machine Learning for Complex and Unmanned Systems
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