Recent Metaheuristics Algorithms for Parameter Identification - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recent Metaheuristics Algorithms for Parameter Identification write by Erik Cuevas. This book was released on 2019-09-03. Recent Metaheuristics Algorithms for Parameter Identification available in PDF, EPUB and Kindle. This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems. It also bridges the gap between recent metaheuristic techniques and interesting identification system methods that benefit from the convenience of metaheuristic schemes by explaining basic ideas of the proposed applications in ways that can be understood by readers new to these fields. As such it is a valuable resource for energy practitioners who are not researchers in metaheuristics. In addition, it offers members of the metaheuristic community insights into how system identification and energy problems can be translated into optimization tasks.
Metaheuristics in Machine Learning: Theory and Applications
Metaheuristics in Machine Learning: Theory and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Metaheuristics in Machine Learning: Theory and Applications write by Diego Oliva. This book was released on . Metaheuristics in Machine Learning: Theory and Applications available in PDF, EPUB and Kindle. This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
Introduction to AI Techniques for Renewable Energy System
Introduction to AI Techniques for Renewable Energy System - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to AI Techniques for Renewable Energy System write by Suman Lata Tripathi. This book was released on 2021-11-25. Introduction to AI Techniques for Renewable Energy System available in PDF, EPUB and Kindle. Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.
Metaheuristics Algorithms in Power Systems
Metaheuristics Algorithms in Power Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Metaheuristics Algorithms in Power Systems write by Erik Cuevas. This book was released on 2019-01-11. Metaheuristics Algorithms in Power Systems available in PDF, EPUB and Kindle. This book discusses the use of efficient metaheuristic algorithms to solve diverse power system problems, providing an overview of the various aspects of metaheuristic methods to enable readers to gain a comprehensive understanding of the field and of conducting studies on specific metaheuristic algorithms related to power-system applications. By bridging the gap between recent metaheuristic techniques and novel power system methods that benefit from the convenience of metaheuristic methods, it offers power system practitioners who are not metaheuristic computation researchers insights into the techniques, which go beyond simple theoretical tools and have been adapted to solve important problems that commonly arise. On the other hand, members of the metaheuristic computation community learn how power engineering problems can be translated into optimization tasks, and it is also of interest to engineers and application developers. Further, since each chapter can be read independently, the relevant information can be quickly found. Power systems is a multidisciplinary field that addresses the multiple approaches used for design and analysis in areas ranging from signal processing, and electronics to computational intelligence, including the current trend of metaheuristic computation.
Recent Developments in Metaheuristics
Recent Developments in Metaheuristics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recent Developments in Metaheuristics write by Lionel Amodeo. This book was released on 2017-09-18. Recent Developments in Metaheuristics available in PDF, EPUB and Kindle. This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.
