Computational Intelligence in Optimization

Applications and Implementations
Herausgegeben:Tenne, Yoel; Goh, Chi-Keong

• Gebundenes Buch

Produktbeschreibung

This volume presents a collection of recent studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world problems. Topics covered include: Intelligent agent-based algorithms, Hybrid intelligent systems, Cognitive and evolutionary robotics, Knowledge-Based Engineering, fuzzy sets and systems, Bioinformatics and Bioengineering, Computational finance and Computational economics, Data mining, Machine learning, and Expert systems. "Computational Intelligence in Optimization" is a comprehensive reference for researchers, practitioners and advanced-level students interested in both the theory and practice of using computational intelligence in real-world applications.

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Produktdetails

• Adaptation, Learning, and Optimization 7
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 12738236, 978-3-642-12774-8
• 2010
• Seitenzahl: 432
• Erscheinungstermin: 9. Juni 2010
• Englisch
• Abmessung: 241mm x 160mm x 31mm
• Gewicht: 892g
• ISBN-13: 9783642127748
• ISBN-10: 3642127746
• Artikelnr.: 29165730

Inhaltsangabe

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.