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Evolutionary Algorithms and Neural Networks

optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as;

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Evolutionary Machine Learning Techniques

machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic;

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Evolutionary Machine Learning Techniques

machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic;

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Combinatorial Development of Solid Catalytic Materials

optimization and artificial neural networks - are described. The book is unique in that it describes evolutionary optimization in a broader context;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity;

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Computational Intelligence Paradigms

neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;

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Computational Intelligence Paradigms

neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;

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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms

We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid;

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Soft Computing

synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three;

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Computational Intelligence

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the;

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Evolutionary Programming IV

academia, industry, and defense. The papers describe both the theory and practical application of evolutionary programming, as well as other;

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Advances in Swarm and Computational Intelligence

separation; swarm interaction behavior; parameters and system optimization; neural networks; evolutionary and genetic algorithms; fuzzy systems;

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Advances in Swarm and Computational Intelligence

separation; swarm interaction behavior; parameters and system optimization; neural networks; evolutionary and genetic algorithms; fuzzy systems;

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Advances in Swarm and Computational Intelligence

separation; swarm interaction behavior; parameters and system optimization; neural networks; evolutionary and genetic algorithms; fuzzy systems;

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Neural Networks in Finance

This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used;

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Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

This book describes recent advances on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and;

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Artificial Intelligence and Evolutionary Computations in Engineering Systems

This book gathers selected papers presented at the 4th International Conference on Artificial Intelligence and Evolutionary Computations;

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Blind Equalization in Neural Networks

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms;

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Artificial Intelligence and Evolutionary Computations in Engineering Systems

This book gathers selected papers presented at the 6th International Conference on Artificial Intelligence and Evolutionary Computations;

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Learning in Energy-Efficient Neuromorphic Computing - Algorithm and Architecture Co-Design

Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning;

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Neural Network Models of Cognition

neuroscience as population genetics for evolutionary science. The volume is divided into six sections, each of which includes both experimental and;

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Evolutionary Algorithms For Mobile Ad Hoc Networks

Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers;

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Intelligent Computing and Applications

neural networks, fuzzy systems, evolutionary algorithms, hybrid intelligent systems, uncertain reasoning techniques, and other machine learning;

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Intelligent System Applications In Power Engineering

This text on evolutionary computation presents an account of neural network and evolutionary programming applications as optimization;

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Applied Evolutionary Algorithms for Engineers using Python

This book meant for those who seek to apply evolutionary algorithms to problems in engineering and science. To this end, it provides the;

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Hands-On Neuroevolution with Python

Increase the performance of various neural network architectures using NEAT, HyperNEAT, ES-HyperNEAT, Novelty Search, SAFE, and deep;

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Artificial Neural Networks and Evolutionary Computation in Remote Sensing

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