Computational Intelligence in Optimization Applications and Implementations /
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 evolutiona...
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| Institutionell upphovsman: | |
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| Övriga upphovsmän: | , |
| Materialtyp: | Elektronisk E-bok |
| Språk: | English |
| Publicerad: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2010.
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| Upplaga: | 1st ed. 2010. |
| Serie: | Adaptation, Learning, and Optimization,
7 |
| Ämnen: | |
| Länkar: | https://doi.org/10.1007/978-3-642-12775-5 |
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Innehållsförteckning:
- 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.