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Springer Intelligence Systems in Environmental Management - Theory & Applications

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Description

Intelligence Systems in Environmental Management: Theory and Applications is a comprehensive reference guide from Springer that addresses complex environmental challenges where conventional techniques fall short. This volume, part of the Intelligent Systems Reference Library series (Volume 113), brings together contributions from prominent researchers to present both foundational and advanced concepts in intelligent systems. The book covers a diverse range of computational approaches including ant colony optimisation, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making, particle swarm optimisation, agent-based modelling, artificial neural networks, simulated annealing, and Tabu search methods. Each chapter provides practical insights into how these intelligent systems can be applied to solve real-world environmental problems, making it an invaluable resource for researchers, academics, and professionals working in environmental science, computer science, and related fields seeking to understand and implement advanced computational intelligence techniques.

Key Features

Springer's comprehensive guide covers both fundamental and advanced intelligence systems concepts applicable to environmental management challenges.

Features contributions from prominent researchers presenting practical applications of ant colony, genetic algorithms, and evolutionary algorithms.

Includes detailed coverage of fuzzy multi-criteria decision making tools and particle swarm optimisation methods for environmental problem-solving.

Explores agent-based modelling, artificial neural networks, simulated annealing, and Tabu search as intelligent solutions for complex environmental systems.

Part of the Intelligent Systems Reference Library series (Volume 113), providing a structured approach to computational intelligence in environmental contexts.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
14 June 2018
Listed Since
14 June 2018

Barcode

No barcode data available

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