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Springer Handbook of Nature-Inspired Optimization Algorithms

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Description

Explore the current state of the art in computational intelligence with the Handbook of Nature-Inspired Optimization Algorithms. Published by Springer, this academic volume focuses on solving single objective bound-constrained real-parameter problems. It serves as a comprehensive resource for those studying complex systems, decision-making, and control processes. As part of the Systems, Decision and Control series, this book provides a deep look into the methodologies used to address modern optimization challenges. Whether you are a researcher, student, or professional in the field of computer science, this text offers the technical foundation needed to understand how nature-inspired methods can be applied to real-world mathematical problems. This volume is designed to support advanced learning and research in AI and machine learning applications.

Key Features

Covers single objective bound-constrained real-parameter optimization methods.

Part of the professional Systems, Decision and Control series by Springer.

Focuses on the state of the art in nature-inspired computational algorithms.

Designed for advanced study in computer science and machine learning.

Provides technical insights for solving complex mathematical problems.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
02 September 2023
Listed Since
05 August 2023

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