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Multi-Objective Swarm Intelligent Systems [electronic resource] :Theory & Experiences / edited by Nadia Nedjah, Leandro Santos Coelho, Luiza Macedo Mourelle.

by Nedjah, Nadia [editor.]; Santos Coelho, Leandro [editor.]; Macedo Mourelle, Luiza [editor.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 261Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010.Description: online resource.ISBN: 9783642051654.Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)DDC classification: 519 Online resources: Click here to access online
Contents:
Multiobjective Gaussian Particle Swarm Approach Applied to Multi-loop PI Controller Tuning of a Quadruple-Tank System -- A Non-ordered Rule Induction Algorithm through Multi-Objective Particle Swarm Optimization: Issues and Applications -- Use of Multiobjective Evolutionary Algorithms in Water Resources Engineering -- Micro-MOPSO: A Multi-Objective Particle Swarm Optimizer That Uses a Very Small Population Size -- Dynamic Multi-objective Optimisation Using PSO -- Meta-PSO for Multi-Objective EM Problems -- Multi-Objective Wavelet-Based Pixel-Level Image Fusion Using Multi-Objective Constriction Particle Swarm Optimization -- Multi-objective Damage Identification Using Particle Swarm Optimization Techniques.
In: Springer eBooksSummary: The editors of this volume, Nadia Nedjah, Leandro dos Santos Coelho and Luiza de Macedo Mourelle, have done a superb job of assembling some of the most innovative and intriguing applications and additions to the methodology and theory of multi-objective swarm intelligence — the immitation of social swarms behaviors for the solution of optimization problems with respect to many criteria.
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Multiobjective Gaussian Particle Swarm Approach Applied to Multi-loop PI Controller Tuning of a Quadruple-Tank System -- A Non-ordered Rule Induction Algorithm through Multi-Objective Particle Swarm Optimization: Issues and Applications -- Use of Multiobjective Evolutionary Algorithms in Water Resources Engineering -- Micro-MOPSO: A Multi-Objective Particle Swarm Optimizer That Uses a Very Small Population Size -- Dynamic Multi-objective Optimisation Using PSO -- Meta-PSO for Multi-Objective EM Problems -- Multi-Objective Wavelet-Based Pixel-Level Image Fusion Using Multi-Objective Constriction Particle Swarm Optimization -- Multi-objective Damage Identification Using Particle Swarm Optimization Techniques.

The editors of this volume, Nadia Nedjah, Leandro dos Santos Coelho and Luiza de Macedo Mourelle, have done a superb job of assembling some of the most innovative and intriguing applications and additions to the methodology and theory of multi-objective swarm intelligence — the immitation of social swarms behaviors for the solution of optimization problems with respect to many criteria.

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