Adaptation and Hybridization in Computational Intelligence (eBook, PDF)
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This carefully edited book takes a walk through recent advances in adaptation andhybridization in the Computational Intelligence (CI) domain. It consists of ten chapters thatare divided into three parts. The first part illustrates background information and providessome theoretical foundation tackling the CI domain, the second partdeals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI.This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are co...
This carefully edited book takes a walk through recent advances in adaptation and
hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that
are divided into three parts. The first part illustrates background information and provides
some theoretical foundation tackling the CI domain, the second part
deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI.
This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization,
modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence -based algorithms.
hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that
are divided into three parts. The first part illustrates background information and provides
some theoretical foundation tackling the CI domain, the second part
deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI.
This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization,
modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence -based algorithms.
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