Computational Intelligence in Optimization

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

• Broschiertes 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.

Produktdetails

• Adaptation, Learning, and Optimization 7
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-642-26361-3
• 2010
• Seitenzahl: 432
• Erscheinungstermin: 5. September 2012
• Englisch
• Abmessung: 235mm x 155mm x 24mm
• Gewicht: 651g
• ISBN-13: 9783642263613
• ISBN-10: 3642263615
• Artikelnr.: 36064888

Inhaltsangabe

Systolic VLSI and FPGA Realization of Artificial Neural Networks.- The structure and use of opposition for decreasing function evaluations in population-based search.- A Review of Agent-Based Co-Evolutionary Algorithms for Multi-Objective Optimization.- New Hybrid Intelligent Systems to Solve Linear and Quadratic Optimization Problems and Increase Guaranteed Optimal Convergence speed of Recurrent ANN.- Optimization problems with cardinality constraints.- From Simulation to Hardware: Towards Real-World Implementation of Evolvable Neural Network-Based Multirobot Controllers.- Optimization with Clifford Support Vector Machines and applications.- A Classification method based on principle component analysis and differential evolution algorithm applied for prediction diagnosis from clinical EMR heart data bases.- Railway Timetable Problems.- Learning to Optimize: Intelligent Global Optimization using Support Vector Machines.- Project Scheduling: Time-cost tradeoff problems.- A Game Theory-Based Multi-Agent System for Expensive Optimisation Problems.- Search Procedure Exploiting Local Regularized Objective Approximation (SPELROA).