Computational Intelligence in Reliability Engineering

1. Front Matter

   Pages I-XIV

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2. The Ant Colony Paradigm for Reliable Systems Design

   • Yun-Chia Liang, Alice E. Smith

   Pages 1-20

3. Modified Great Deluge Algorithm versus Other Metaheuristics in Reliability Optimization

   • Vadlamani Ravi

   Pages 21-36

4. Applications of the Cross-Entropy Method in Reliability

   • Dirk P. Kroese, Kin-Ping Hui

   Pages 37-82

5. Particle Swarm Optimization in Reliability Engineering

   • Gregory Levitin, Xiaohui Hu, Yuan-Shun Dai

   Pages 83-112

6. Cellular Automata and Monte Carlo Simulation for Network Reliability and Availability Assessment

   • Claudio M. Rocco S., Enrico Zio

   Pages 113-144

7. Network Reliability Assessment through Empirical Models using a Machine Learning Approach

   • Claudio M. Rocco S., Marco Muselli

   Pages 145-174

8. Neural Networks for Reliability-Based Optimal Design

   • Ming J Zuo, Zhigang Tian, Hong-Zhong Huang

   Pages 175-196

9. Software Reliability Predictions using Artificial Neural Networks

   • Q. P. Hu, M. Xie, S. H. Ng

   Pages 197-222

10. Computation Intelligence in Online Reliability Monitoring

    • Ratna Babu Chinnam, Bharatendra Rai

    Pages 223-260

11. Imprecise Reliability: An Introductory Overview

    • Lev V. Utkin, Frank P. A. Coolen

    Pages 261-306

12. Posbist Reliability Theory for Coherent Systems

    • Hong-Zhong Huang, Xin Tong, Ming J Zuo

    Pages 307-346

13. Analyzing Fuzzy System Reliability Based on the Vague Set Theory

    • Shyi-Ming Chen

    Pages 347-362

14. Fuzzy Sets in the Evaluation of Reliability

    • Olgierd Hryniewicz

    Pages 363-386

15. Grey Differential Equation GM(1,1) Models in Repairable System Modeling

    • Renkuan Guo

    Pages 387-413

This two volume book covers the recent applications of computational intelli gence techniques in reliability engineering. Research in the area of computational intelligence is growing rapidly due to the many successful applications of these new techniques in very diverse problems. “Computational Intelligence” covers many fields such as neural networks, fu zzy logic, evolutionary computing, and their hybrids and derivatives. Many indus tries have benefited from adopting this technology. The increased number of patents and diverse range of products devel oped using computational intelligence methods is evidence of this fact. These techniques have attracted increasing attention in recent years for solving many complex problems. They are inspired by nature, biology, statistical tech niques, physics and neuroscience. They have been successfully applied in solving many complex problems where traditional problem solving methods have failed. The book aims to be a repository for the current and cutting edge applications of computational intelligent techniques in reliability analysis and optimization.

• algorithm
• algorithms
• artificial neural network
• automata
• fuzzy
• heuristics
• intelligence
• learning
• metaheuristic
• network
• networks
• neural networks
• optimization
• reliability
• reliability engineering
• quality control, reliability, safety and risk

• Research & Development Division, The Israel Electronic Corporation Ltd., Haifa, Israel

  Gregory Levitin

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