Autorentext

Nazmul Siddique obtained Dipl.-Ing degree from Dresden University of Technology, Germany in Cybernetics, M. Sc. in Computer Science from Bangladesh University of Engineering and Technology, and PhD in intelligent control from the Department of Automatic Control and Systems Engineering, University of Sheffield. Dr Siddique is a Lecturer in the School of Computing and Intelligent Systems, Ulster University. He has published over 150 research papers including three books. He has been involved in organizing many national and international conferences. He is on the editorial board of the Journal of Behavioral Robotics, Engineering Letters, International Journal of Machine Learning and Cybernetics, International Journal of Applied Pattern Recognition, International Journal of Advances in Robotics Research and also on the editorial advisory board of the International Journal of Neural Systems. He is a senior member of the IEEE, and a member of executive committee of IEEE SMC UK-RI Chapter.

Hojjat Adeli is Professor of Civil, Environmental, and Geodetic Engineering, and by courtesy Professor of Biomedical Engineering, Biomedical Informatics, Neuroscience, and Neurology at The Ohio State University. He has authored over 550 research publications including 15 books since he received his Ph.D. from Stanford University in 1976. He has presented Keynote Lectures at 103 conferences held in 43 different countries. Among his numerous awards include the University Distinguished Scholar Award "in recognition of extraordinary accomplishment in research and scholarship," the Peter L. and Clara M. Scott Award for Excellence in Engineering Education and Charles E. MacQuigg Outstanding Teaching Award" from The Ohio State University, the ASCE Construction Management Award, a Special Medal in Recognition of Outstanding Contribution to the Development of Computational Intelligence from The Polish Neural Network Society, Eduardo Renato Caianiello Award for Excellence in Scientific Research from Italian Society of Neural Networks, an Honorary Doctorate from Vilnius Gediminas Technical University, Lithuania, and membership in the Spanish Royal Engineering Society. In 2010, he was profiled as Engineering Legend in the ASCE journal of Leadership and Management in Engineering. He is a Distinguished Member of ASCE, and a Fellow of AAAS, IEEE, AIMBE, and the American Neurological Association.

Klappentext

Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a comprehensive introduction to the methodologies and algorithms in nature-inspired computing, with an emphasis on applications to real-life engineering problems.

The research interest for Nature-inspired Computing has grown considerably exploring different phenomena observed in nature and basic principles of physics, chemistry, and biology. The discipline has reached a mature stage and the field has been well-established. The inspiration of writing this book on Nature-inspired Computing in three volumes came from the book, Machine Learning - Neural Networks, Genetic Algorithms, and Fuzzy Systems, Hojjat Adeli and S.L. Hung (John Wiley and Sons, 1995) as the first treatise that presented the three main fields of computational intelligence in a single book. That led the authors first to write the book, Computational Intelligence - Synergies of Fuzzy Logic, Neural Networks, and Evolutionary Computing, Nazmul Siddique and Hojjat Adeli (John Wiley and Sons, 2013.) This endeavor is another attempt at investigation into various computational schemes inspired from nature, which are presented in this book with the development of a suitable framework and industrial applications.

Designed for senior undergraduates, postgraduates, research students, and professionals, the book is written at a comprehensible level for students who have some basic knowledge of calculus and differential equations, and some exposure to optimization theory. Due to the focus on search and optimization, the book is also appropriate for electrical, control, civil, industrial and manufacturing engineering, business, and economics students, as well as those in computer and information sciences.

The book can also serve as a reference for researchers and scientists in the fields of sytem science, natural computing, and optimization.

Zusammenfassung

Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a comprehensive introduction to the methodologies and algorithms in nature-inspired computing, with an emphasis on applications to real-life engineering problems.

The research interest for Nature-inspired Computing has grown considerably exploring different phenomena observed in nature and basic principles of physics, chemistry, and biology. The discipline has reached a mature stage and the field has been well-established. This endeavour is another attempt at investigation into various computational schemes inspired from nature, which are presented in this book with the development of a suitable framework and industrial applications.

Designed for senior undergraduates, postgraduates, research students, and professionals, the book is written at a comprehensible level for students who have some basic knowledge of calculus and differential equations, and some exposure to optimization theory. Due to the focus on search and optimization, the book is also appropriate for electrical, control, civil, industrial and manufacturing engineering, business, and economics students, as well as those in computer and information sciences.

With the mathematical and programming references and applications in each chapter, the book is self-contained, and can also serve as a reference for researchers and scientists in the fields of system science, natural computing, and optimization.

Inhalt

Swarm Intelligence-Based Algorithms. Bio-Inspired Algorithms. Physics and Chemistry-Based Algorithms.