Tenne / Goh Computational Intelligence in Optimization

Applications and Implementations
1. Auflage 2010
ISBN: 978-3-642-12775-5
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 7, 412 Seiten, eBook

Reihe: Evolutionary Learning and Optimization

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.

Zielgruppe

Research

Autoren/Hrsg.

Tenne, Yoel

Goh, Chi-Keong

Inhaltsverzeichnis

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.