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Springer Parallel and Distributed Computational Intelligence - Studies 269

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Description

Parallel and Distributed Computational Intelligence: 269 is a comprehensive academic text published by Springer that explores advanced computational methods across distributed systems and evolutionary algorithms. This volume covers scaling genetic algorithms through data-intensive computing, evolvable agents in peer-to-peer frameworks, and evolutionary algorithms deployed on volunteer computing platforms like MilkyWay@Home. The book examines swarm intelligence approaches to on-chip parallel computing, large-scale bioinformatics data mining leveraging graphics processing units, and parallel estimation of distribution algorithms. Readers will discover practical applications of parallel multi-objective optimisation using self-organised heterogeneous resources. This text is essential for researchers, practitioners, and students working in artificial intelligence, machine learning, and computational intelligence who need to understand modern approaches to scaling algorithms across distributed and parallel computing environments.

Key Features

Parallel and Distributed Computational Intelligence volume covers scaling genetic algorithms using data-intensive computing techniques for handling large datasets efficiently.

The book explores evolvable agents and peer-to-peer evolutionary algorithm frameworks that enable distributed processing across networked systems.

Springer's publication includes practical examples from volunteer computing platforms such as MilkyWay@Home demonstrating real-world distributed algorithm deployment.

Advanced topics include large-scale bioinformatics data mining with parallel genetic programming optimised for graphics processing units and GPU acceleration.

The text addresses parallel multi-objective optimisation methods using self-organised heterogeneous resources to balance competing objectives in distributed environments.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
18 September 2010
Listed Since
27 October 2009

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