Handbook of Research on Soft Computing and Nature-Inspired Algorithms
Handbook of Research on Soft Computing and Nature-Inspired Algorithms

Author: Shandilya, Shishir K.

Publisher: IGI Global

Published: 2017-03-10

Total Pages: 649

ISBN-13: 1522521291

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Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Handbook of Research on Natural Computing for Optimization Problems
Handbook of Research on Natural Computing for Optimization Problems

Author: Mandal, Jyotsna Kumar

Publisher: IGI Global

Published: 2016-05-25

Total Pages: 1199

ISBN-13: 1522500596

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Nature-inspired computation is an interdisciplinary topic area that connects the natural sciences to computer science. Since natural computing is utilized in a variety of disciplines, it is imperative to research its capabilities in solving optimization issues. The Handbook of Research on Natural Computing for Optimization Problems discusses nascent optimization procedures in nature-inspired computation and the innovative tools and techniques being utilized in the field. Highlighting empirical research and best practices concerning various optimization issues, this publication is a comprehensive reference for researchers, academicians, students, scientists, and technology developers interested in a multidisciplinary perspective on natural computational systems.

Handbook of Nature-Inspired and Innovative Computing
Handbook of Nature-Inspired and Innovative Computing

Author: Albert Y. Zomaya

Publisher: Springer Science & Business Media

Published: 2006-01-10

Total Pages: 758

ISBN-13: 9780387405322

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As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications. This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.

Nature-Inspired Computation and Swarm Intelligence
Nature-Inspired Computation and Swarm Intelligence

Author: Xin-She Yang

Publisher: Academic Press

Published: 2020-04-10

Total Pages: 442

ISBN-13: 0128197145

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Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence.

Handbook of Research on Novel Soft Computing Intelligent Algorithms
Handbook of Research on Novel Soft Computing Intelligent Algorithms

Author: Pandian Vasant

Publisher: IGI Global

Published: 2013-08-31

Total Pages: 1173

ISBN-13: 1466644516

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"This book explores emerging technologies and best practices designed to effectively address concerns inherent in properly optimizing advanced systems, demonstrating applications in areas such as bio-engineering, space exploration, industrial informatics, information security, and nuclear and renewable energies"--Provided by publisher.

Handbook of Research on Soft Computing and Nature-inspired Algorithms
Handbook of Research on Soft Computing and Nature-inspired Algorithms

Author: Shishir K. Shandilya

Publisher: Information Science Reference

Published: 2017

Total Pages: 0

ISBN-13: 9781522521303

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Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2016-07-26

Total Pages: 1810

ISBN-13: 1522507892

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As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.

Handbook of Research on Artificial Intelligence Techniques and Algorithms
Handbook of Research on Artificial Intelligence Techniques and Algorithms

Author: Vasant, Pandian

Publisher: IGI Global

Published: 2014-11-30

Total Pages: 913

ISBN-13: 1466672595

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For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.

Recent Advances of Hybrid Intelligent Systems Based on Soft Computing
Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

Author: Patricia Melin

Publisher: Springer Nature

Published: 2020-11-06

Total Pages: 341

ISBN-13: 3030587282

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This book describes recent advances on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There are also some papers that present theory and practice of meta-heuristics in different areas of application. Another group of papers describes diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.