Evolutionary Algorithms In Intelligent Systems


Evolutionary Algorithms In Intelligent Systems
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Evolutionary Algorithms In Intelligent Systems


Evolutionary Algorithms In Intelligent Systems
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Author : Alfredo Milani
language : en
Publisher: MDPI
Release Date : 2020-12-07

Evolutionary Algorithms In Intelligent Systems written by Alfredo Milani and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-07 with Technology & Engineering categories.


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.



Evolutionary Algorithms In Intelligent Systems


Evolutionary Algorithms In Intelligent Systems
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Author : Alfredo Milani
language : en
Publisher:
Release Date : 2020

Evolutionary Algorithms In Intelligent Systems written by Alfredo Milani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.


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.



Evolutionary Computation With Intelligent Systems


Evolutionary Computation With Intelligent Systems
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Author : R.S. Chauhan
language : en
Publisher: CRC Press
Release Date : 2022-03-29

Evolutionary Computation With Intelligent Systems written by R.S. Chauhan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-29 with Technology & Engineering categories.


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.



Intelligent Systems


Intelligent Systems
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Author : Vladimir M. Koleshko
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-03-02

Intelligent Systems written by Vladimir M. Koleshko and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-02 with Computers categories.


This book is dedicated to intelligent systems of broad-spectrum application, such as personal and social biosafety or use of intelligent sensory micro-nanosystems such as "e-nose", "e-tongue" and "e-eye". In addition to that, effective acquiring information, knowledge management and improved knowledge transfer in any media, as well as modeling its information content using meta-and hyper heuristics and semantic reasoning all benefit from the systems covered in this book. Intelligent systems can also be applied in education and generating the intelligent distributed eLearning architecture, as well as in a large number of technical fields, such as industrial design, manufacturing and utilization, e.g., in precision agriculture, cartography, electric power distribution systems, intelligent building management systems, drilling operations etc. Furthermore, decision making using fuzzy logic models, computational recognition of comprehension uncertainty and the joint synthesis of goals and means of intelligent behavior biosystems, as well as diagnostic and human support in the healthcare environment have also been made easier.



Engineering Evolutionary Intelligent Systems


Engineering Evolutionary Intelligent Systems
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Author : Ajith Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-03

Engineering Evolutionary Intelligent Systems written by Ajith Abraham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-03 with Computers categories.


This edited volume deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business and commerce. It comprises 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.



Artificial Intelligence And Evolutionary Algorithms In Engineering Systems


Artificial Intelligence And Evolutionary Algorithms In Engineering Systems
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Author : L Padma Suresh
language : en
Publisher: Springer
Release Date : 2014-11-25

Artificial Intelligence And Evolutionary Algorithms In Engineering Systems written by L Padma Suresh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-25 with Technology & Engineering categories.


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.



Evolutionary Robotics


Evolutionary Robotics
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Author : Lingfeng Wang
language : en
Publisher: World Scientific
Release Date : 2006

Evolutionary Robotics written by Lingfeng Wang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Technology & Engineering categories.


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.



Computational Intelligence


Computational Intelligence
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Author : Christine L. Mumford
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-21

Computational Intelligence written by Christine L. Mumford and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-21 with Computers categories.


This book is about synergy in computational intelligence (CI). It is a c- lection of chapters that covers a rich and diverse variety of computer-based techniques, all involving some aspect of computational intelligence, but each one taking a somewhat pragmatic view. Many complex problems in the real world require the application of some form of what we loosely call “intel- gence”fortheirsolution. Fewcanbesolvedbythenaiveapplicationofasingle technique, however good it is. Authors in this collection recognize the li- tations of individual paradigms, and propose some practical and novel ways in which di?erent CI techniques can be combined with each other, or with more traditional computational techniques, to produce powerful probl- solving environments which exhibit synergy, i. e. , systems in which the whole 1 is greater than the sum of the parts . Computational intelligence is a relatively new term, and there is some d- agreement as to its precise de?nition. Some practitioners limit its scope to schemes involving evolutionary algorithms, neural networks, fuzzy logic, or hybrids of these. For others, the de?nition is a little more ?exible, and will include paradigms such as Bayesian belief networks, multi-agent systems, case-based reasoning and so on. Generally, the term has a similar meaning to the well-known phrase “Arti?cial Intelligence” (AI), although CI is p- ceived moreas a “bottom up” approachfrom which intelligent behaviour can emerge,whereasAItendstobestudiedfromthe“topdown”,andderivefrom pondering upon the “meaning of intelligence”. (These and other key issues will be discussed in more detail in Chapter 1.



Research And Development In Intelligent Systems Xxviii


Research And Development In Intelligent Systems Xxviii
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Author : Max Bramer
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-11-13

Research And Development In Intelligent Systems Xxviii written by Max Bramer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-13 with Computers categories.


The papers in this volume are the refereed papers presented at AI-2011, the Thirty-first SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2011 in both the technical and the application streams. They present new and innovative developments and applications, divided into technical stream sections on Planning, Evolutionary Algorithms, Speech and Vision, and Machine Learning, followed by application stream sections on Knowledge Discovery and Data Mining, Machine Learning, Evolutionary Algorithms and AI in Action. The volume also includes the text of short papers presented as posters at the conference. This is the twenty-eighth volume in the Research and Development in Intelligent Systems series, which also incorporates the nineteenth volume in the Applications and Innovations in Intelligent Systems series. These series are essential reading for those who wish to keep up to date with developments in this important field.



Evolutionary Machine Learning Techniques


Evolutionary Machine Learning Techniques
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Author : Seyedali Mirjalili
language : en
Publisher: Springer Nature
Release Date : 2019-11-11

Evolutionary Machine Learning Techniques written by Seyedali Mirjalili and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-11 with Technology & Engineering categories.


This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.