Computational Intelligence in Optimization: Applications and Implementations: Adaptation, Learning, and Optimization, cartea 7

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.

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.

State of the art of applications and implementations of computational intelligence in optimization Provides both theoretical treatments and real-world insights gained by experience in computational intelligence in optimization Comprehensive reference for researchers, practitioners and graduate students interested in both the theory and practice of using computational intelligence in real-world applications