Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition

Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition

For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores...

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Bibliographic Details
Published in:Springer eBooks
Main Authors: Kiranyaz, Serkan (Author), Ince, Turker (Author), Gabbouj, Moncef (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Series:Adaptation, Learning, and Optimization,
Subjects:
Computer Science.
Artificial intelligence.
engineering.
Computer engineering.
Artificial Intelligence (incl. Robotics).
Computational Intelligence.
electrical engineering.
Online Access:http://dx.doi.org/10.1007/978-3-642-37846-1
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Table of Contents:
  • Chap. 1 Introduction
  • Chap. 2 Optimization Techniques
  • Chap. 3 Particle Swarm Optimization
  • Chap. 4 Multidimensional Particle Swarm Optimization
  • Chap. 5 Improving Global Convergence
  • Chap. 6 Dynamic Data Clustering
  • Chap. 7 Evolutionary Artificial Neural Networks
  • Chap. 8 Personalized ECG Classification
  • Chap. 9 Image Classification Through a Collective Network of Binary Classifiers
  • Chap. 10 Evolutionary Feature Synthesis for Image Retrieval.

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