Computational Intelligence in Reliability Engineering: Evolutionary Techniques in Reliability Analysis and Optimization

Recent Advances in Optimal Reliability Allocation.- Multiobjective Metaheuristic Approaches to Reliability Optimization.- Genetic Algorithm Applications in Surveillance and Maintenance Optimization.- Genetic Algorithms and Monte Carlo Simulation for the Optimization of System Design and Operation.- New Evolutionary Methodologies for Integrated Safety System Design and Maintenance Optimization.- Optimal Redundancy Allocation of Multi-State Systems with Genetic Algorithms.- Intelligent Interactive Multiobjective Optimization of System Reliability.- Reliability Assessment of Composite Power Systems Using Genetic Algorithms.- Genetic Optimization of Multidimensional Technological Process Reliability.- Scheduling Multiple-version Programs on Multiple Processors.- Redundancy Optimization Problems with Uncertain Lifetimes.- Computational Intelligence Methods in Software Reliability Prediction.

[1]  Vladimir Vapnik,et al.  An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.

[2]  Liang Tian,et al.  Evolutionary neural network modeling for software cumulative failure time prediction , 2005, Reliab. Eng. Syst. Saf..

[3]  Roy Billinton,et al.  A comparison of Monte Carlo simulation techniques for composite power system reliability assessment , 1995, IEEE WESCANEX 95. Communications, Power, and Computing. Conference Proceedings.

[4]  Masatoshi Sakawa,et al.  Multiobjective reliability and redundancy optimization of a series-parallel system by the Surrogate Worth Trade-off method , 1978 .

[5]  Lorraine R. Gardiner,et al.  Unified interactive multiple objective programming , 1994 .

[6]  Chanan Singh,et al.  An efficient technique for reliability analysis of power systems including time dependent sources , 1988 .

[7]  Chanan Singli,et al.  Generation System Reliability Evaluation Using a Cluster Based Load Model , 1989 .

[8]  Singiresu S Rao,et al.  Reliability and redundancy apportionment using crisp and fuzzy multiobjective optimization approaches , 1992 .

[9]  Ralph E. Steuer,et al.  A Heuristic for Estimating Nadir Criterion Values in Multiple Objective Linear Programming , 1997, Oper. Res..

[10]  Chanan Singh,et al.  Pruning and simulation for determination of frequency and duration indices of composite power systems , 1999 .

[11]  Liang Tian,et al.  A novel approach for short-term load forecasting using support vector machines , 2004, Int. J. Neural Syst..

[12]  Shigeru Yamada,et al.  TESTING-DOMAIN DEPENDENT SOFTWARE RELIABILITY GROWTH MODELS AND THEIR COMPARISONS OF GOODNESS-OF-FIT , 2001 .

[13]  Liang Tian,et al.  DYNAMIC SOFTWARE RELIABILITY PREDICTION: AN APPROACH BASED ON SUPPORT VECTOR MACHINES , 2005 .

[14]  C. Singh,et al.  Rules for Calculating the Time-Specific Frequency of System Failure , 1981, IEEE Transactions on Reliability.

[15]  Kyung S. Park.  Fuzzy Apportionment of System Reliability , 1987, IEEE Transactions on Reliability.

[16]  Masatoshi Sakawa.  Interactive Multiobjective Optimization by the Sequential Proxy Optimization Technique (SPOT) , 1982, IEEE Transactions on Reliability.

[17]  Minghe Sun,et al.  Solving Multiple Objective Programming Problems Using Feed-Forward Artificial Neural Networks: The Interactive FFANN Procedure , 1996 .

[18]  Xiaolin Teng,et al.  Considering fault removal efficiency in software reliability assessment , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[19]  R. Sitte.  Comparison of software-reliability-growth predictions: neural networks vs parametric-recalibration , 1999 .

[20]  Ping Guo,et al.  Support Vector Regression for Software Reliability Growth Modeling and Prediction , 2005, ISNN.

[21]  Boriana L. Milenova,et al.  Fuzzy and neural approaches in engineering , 1997 .

[22]  Afzel Noore,et al.  Software Reliability Prediction Using Recurrent Neural Network With Bayesian Regularization , 2004, Int. J. Neural Syst..

[23]  Hoang Pham,et al.  Exploratory analysis of environmental factors for enhancing the software reliability assessment , 2001, J. Syst. Softw..

[24]  A. M. Leite da Silva,et al.  A conditional probability approach to the calculation of frequency and duration indices in composite reliability evaluation , 1993 .

[25]  Minghe Sun,et al.  Artificial neural network representations for hierarchical preference structures , 1996, Comput. Oper. Res..

[26]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[27]  Hans-Jürgen Zimmermann,et al.  Fuzzy global optimization of complex system reliability , 2000, IEEE Trans. Fuzzy Syst..

[28]  Chanan Singh,et al.  Improved Algorithms for Multi-Area Reliability Evaluation Using the Decomposition-Simulation Approach , 1989, IEEE Power Engineering Review.

[29]  Lev V. Utkin,et al.  A FUZZY SOFTWARE RELIABILITY MODEL WITH MULTIPLE-ERROR INTRODUCTION AND REMOVAL , 2002 .

[30]  Liang Tian,et al.  Modeling distributed software defect removal effectiveness in the presence of code churn , 2005, Math. Comput. Model..

[31]  A. Dhingra.  Optimal apportionment of reliability and redundancy in series systems under multiple objectives , 1992 .

[32]  Hoang Pham,et al.  NHPP software reliability and cost models with testing coverage , 2003, Eur. J. Oper. Res..

[33]  Catherine Stringfellow,et al.  An Empirical Method for Selecting Software Reliability Growth Models , 2002, Empirical Software Engineering.

[34]  Raúl Rojas,et al.  Neural Networks - A Systematic Introduction , 1996 .

[35]  Probability Subcommittee,et al.  IEEE Reliability Test System , 1979, IEEE Transactions on Power Apparatus and Systems.

[36]  Minghe Sun,et al.  Interactive multiple objective programming using Tchebycheff programs and artificial neural networks , 2000, Comput. Oper. Res..

[37]  Toshiyuki Inagaki,et al.  Interactive Optimization of System Reliability Under Multiple Objectives , 1978, IEEE Transactions on Reliability.

[38]  Yong Rae Kwon,et al.  Empirical evaluation of a fuzzy logic-based software quality prediction model , 2002, Fuzzy Sets Syst..

[39]  Wan Seon Shin,et al.  Interactive multiple objective optimization: Survey I - continuous case , 1991, Comput. Oper. Res..

[40]  Hoang Pham,et al.  Software reliability and cost models: Perspectives, comparison, and practice , 2003, Eur. J. Oper. Res..

[41]  Liang Tian,et al.  On-line prediction of software reliability using an evolutionary connectionist model , 2005, J. Syst. Softw..