Computational Intelligence in Optimization: Applications and Implementations by Yoel TenneComputational Intelligence in Optimization: Applications and Implementations by Yoel Tenne

Computational Intelligence in Optimization: Applications and Implementations

byYoel TenneEditorChi-Keong Goh

Paperback | September 5, 2012

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This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging
real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.
Title:Computational Intelligence in Optimization: Applications and ImplementationsFormat:PaperbackDimensions:412 pages, 23.5 × 15.5 × 0.01 inPublished:September 5, 2012Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3642263615

ISBN - 13:9783642263613

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Table of Contents

New Hybrid Intelligent Systems to Solve Linear and Quadratic Optimization Problems and Increase Guaranteed Optimal Convergence Speed of Recurrent ANN.- A Novel Optimization Algorithm Based on Reinforcement Learning.- The Use of Opposition for Decreasing Function Evaluations in Population-Based Search.- Search Procedure Exploiting Locally Regularized Objective Approximation. A Convergence Theorem for Direct Search Algorithms.- Optimization Problems with Cardinality Constraints.- Learning Global Optimization Through a Support Vector Machine Based Adaptive Multistart Strategy.- Multi-Objective Optimization Using Surrogates.- A Review of Agent-Based Co-Evolutionary Algorithms for Multi-Objective Optimization.- A Game Theory-Based Multi-Agent System for Expensive Optimisation Problems.- Optimization with Clifford Support Vector Machines and applications.- A Classification method based on principal component analysis and differential evolution algorithm applied for prediction diagnosis from clinical EMR heart data sets.- An Integrated Approach to Speed Up GA-SVM Feature Selection Model.- Computation in Complex Environments;.- Project Scheduling: Time-Cost Tradeoff Problems.- Systolic VLSI and FPGA Realization of Artificial Neural Networks.- Application of Coarse-Coding Techniques for Evolvable Multirobot Controllers.