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Author: R.S. Chauhan
Publisher: CRC Press
ISBN: 1000550540
Category : Technology & Engineering
Languages : en
Pages : 316
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Book Description
This book focuses on cutting-edge innovations and core theories, principles, and algorithms applicable to a wide area. Real-life applications, case studies, and examples are included along with emerging trends, design, and optimized solutions pivoting around the needs of Society 5.0. Evolutionary Computation with Intelligent Systems: A Multidisciplinary Approach to Society 5.0 provides a holistic view of evolutionary computation techniques including principles, procedures, and future applications with real-life examples. The book comprehensively explains evolutionary computation, design, principles, development trends, and optimization and describes how it can transform the operating context of the organization. It exemplifies the potential of evolutionary computation for the next generation and the role of cloud computing in shaping Society 5.0. It also provides insight into various platforms, paradigms, techniques, and tools used in diverse fields. This book appeals to a variety of readers such as academicians, researchers, research scholars, and postgraduates.
Author: R.S. Chauhan
Publisher: CRC Press
ISBN: 1000550540
Category : Technology & Engineering
Languages : en
Pages : 316
Get Book Here
Book Description
This book focuses on cutting-edge innovations and core theories, principles, and algorithms applicable to a wide area. Real-life applications, case studies, and examples are included along with emerging trends, design, and optimized solutions pivoting around the needs of Society 5.0. Evolutionary Computation with Intelligent Systems: A Multidisciplinary Approach to Society 5.0 provides a holistic view of evolutionary computation techniques including principles, procedures, and future applications with real-life examples. The book comprehensively explains evolutionary computation, design, principles, development trends, and optimization and describes how it can transform the operating context of the organization. It exemplifies the potential of evolutionary computation for the next generation and the role of cloud computing in shaping Society 5.0. It also provides insight into various platforms, paradigms, techniques, and tools used in diverse fields. This book appeals to a variety of readers such as academicians, researchers, research scholars, and postgraduates.
Author: Seyedali Mirjalili
Publisher: Springer
ISBN: 3319930257
Category : Technology & Engineering
Languages : en
Pages : 164
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Book Description
This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
Author: L. Padma Suresh
Publisher: Springer
ISBN: 8132221265
Category : Technology & Engineering
Languages : en
Pages : 831
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Book Description
The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.
Author: Dan Simon
Publisher: John Wiley & Sons
ISBN: 1118659503
Category : Mathematics
Languages : en
Pages : 776
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Book Description
A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear but theoretically rigorous understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs including opposition-based learning, artificial fish swarms, bacterial foraging, and many others and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.
Author: Lingfeng Wang
Publisher: World Scientific
ISBN: 9812773142
Category : Technology & Engineering
Languages : en
Pages : 267
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Book Description
This invaluable book comprehensively describes evolutionary robotics and computational intelligence, and how different computational intelligence techniques are applied to robotic system design. It embraces the most widely used evolutionary approaches with their merits and drawbacks, presents some related experiments for robotic behavior evolution and the results achieved, and shows promising future research directions. Clarity of explanation is emphasized such that a modest knowledge of basic evolutionary computation, digital circuits and engineering design will suffice for a thorough understanding of the material. The book is ideally suited to computer scientists, practitioners and researchers keen on computational intelligence techniques, especially the evolutionary algorithms in autonomous robotics at both the hardware and software levels. Sample Chapter(s). Chapter 1: Artificial Evolution Based Autonomous Robot Navigation (184 KB). Contents: Artificial Evolution Based Autonomous Robot Navigation; Evolvable Hardware in Evolutionary Robotics; FPGA-Based Autonomous Robot Navigation via Intrinsic Evolution; Intelligent Sensor Fusion and Learning for Autonomous Robot Navigation; Task-Oriented Developmental Learning for Humanoid Robots; Bipedal Walking Through Reinforcement Learning; Swing Time Generation for Bipedal Walking Control Using GA Tuned Fuzzy Logic Controller; Bipedal Walking: Stance Ankle Behavior Optimization Using Genetic Algorithm. Readership: Researchers in evolutionary robotics, and graduate and advanced undergraduate students in computational intelligence.
Author: Xinjie Yu
Publisher: Springer Science & Business Media
ISBN: 1849961298
Category : Computers
Languages : en
Pages : 427
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Book Description
Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as: • genetic algorithms, • differential evolution, • swarm intelligence, and • artificial immune systems. The reader is introduced to a range of applications, as Introduction to Evolutionary Algorithms demonstrates how to model real world problems, how to encode and decode individuals, and how to design effective search operators according to the chromosome structures with examples of constraint optimization, multiobjective optimization, combinatorial optimization, and supervised/unsupervised learning. This emphasis on practical applications will benefit all students, whether they choose to continue their academic career or to enter a particular industry. Introduction to Evolutionary Algorithms is intended as a textbook or self-study material for both advanced undergraduates and graduate students. Additional features such as recommended further reading and ideas for research projects combine to form an accessible and interesting pedagogical approach to this widely used discipline.
Author: Crina Grosan
Publisher: Springer Science & Business Media
ISBN: 364221004X
Category : Technology & Engineering
Languages : en
Pages : 456
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Book Description
Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17 chapters offers a step-by-step introduction (in a chronological order) to the various modern computational intelligence tools used in practical problem solving. Staring with different search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligent techniques; the authors illustrate the design of knowledge-based systems and advanced expert systems, which incorporate uncertainty and fuzziness. Machine learning algorithms including decision trees and artificial neural networks are presented and finally the fundamentals of hybrid intelligent systems are also depicted. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques, machine learning and data mining would find the comprehensive coverage of this book invaluable.
Author: Alfredo Milani
Publisher: MDPI
ISBN: 3039436112
Category : Technology & Engineering
Languages : en
Pages : 144
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Book Description
Evolutionary algorithms and metaheuristics are widely used to provide efficient and effective approximate solutions to computationally hard optimization problems. With the widespread use of intelligent systems in recent years, evolutionary algorithms have been applied, beyond classical optimization problems, to AI system parameter optimization and the design of artificial neural networks and feature selection in machine learning systems. This volume will present recent results of applications of the most successful metaheuristics, from differential evolution and particle swarm optimization to artificial neural networks, loT allocation, and multi-objective optimization problems. It will also provide a broad view of the role and the potential of evolutionary algorithms as service components in Al systems.
Author: Jagdish Chand Bansal
Publisher: Springer
ISBN: 3319913417
Category : Technology & Engineering
Languages : en
Pages : 194
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Book Description
This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
Author: Gary B. Fogel
Publisher: Elsevier
ISBN: 0080506089
Category : Computers
Languages : en
Pages : 425
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Book Description
Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researchers in evolutionary computation (EC) have turned their attention to these problems. They understand the power of EC to rapidly search very large and complex spaces and return reasonable solutions. While these researchers are increasingly interested in problems from the biological sciences, EC and its problem-solving capabilities are generally not yet understood or applied in the biology community.This book offers a definitive resource to bridge the computer science and biology communities. Gary Fogel and David Corne, well-known representatives of these fields, introduce biology and bioinformatics to computer scientists, and evolutionary computation to biologists and computer scientists unfamiliar with these techniques. The fourteen chapters that follow are written by leading computer scientists and biologists who examine successful applications of evolutionary computation to various problems in the biological sciences.* Describes applications of EC to bioinformatics in a wide variety of areas including DNA sequencing, protein folding, gene and protein classification, drug targeting, drug design, data mining of biological databases, and biodata visualization.* Offers industrial and academic researchers in computer science, biology, and bioinformatics an important resource for applying evolutionary computation.* Includes a detailed appendix of biological data resources.
