| Application of Improved Genetic Algorithm in Network Fault Diagnosis Expert System |
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| 作者姓名： | 苏利敏 侯朝桢 戴忠健 张雅静 |
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| 作者单位： | DepartmentofAutomaticControl,SchoolofInformationScienceandTechnology,BeijingInstituteofTechnology,Beijing100081,China |
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| 基金项目： | theMinisterialLevelFoundation( 51 40 30 7) |
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| 摘 要： | Knowledge acquisition is the “botdeneck“ of building an expert system. Based on the optimization model, an improved genetic algorithm applied to knowledge acquisition of a network fault diagnostic expert system is proposed. The algorithm applies operators such as selection, crossover and mutation to evolve an initial popula-tion of diagnostic rules. Especially, a self-adaptive method is put forward to regulate the crossover rate and muta-tion rate. In the end, a knowledge acquisition problem of a simple network fault diagnostic system is simulated,the results of simulation show that the improved approach can solve the problem of convergence better.
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| 关 键 词： | 专家系统 知识获取 故障诊断 遗传算法 |
| 收稿时间： | 2002/7/19 0:00:00 |
Application of Improved Genetic Algorithm in Network Fault Diagnosis Expert System |
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| SU Li min,HOU Chao zhen,DAI Zhong jian and ZHANG Ya jing.Application of Improved Genetic Algorithm in Network Fault Diagnosis Expert System[J].Journal of Beijing Institute of Technology,2003,12(3):225-229. |
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| Authors: | SU Li min HOU Chao zhen DAI Zhong jian and ZHANG Ya jing |
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| Affiliation: | Department of Automatic Control, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | Knowledge acquisition is the "bottleneck" of building an expert system. Based on the optimization model, an improved genetic algorithm applied to knowledge acquisition of a network fault diagnostic expert system is proposed. The algorithm applies operators such as selection, crossover and mutation to evolve an initial population of diagnostic rules. Especially, a self-adaptive method is put forward to regulate the crossover rate and mutation rate. In the end, a knowledge acquisition problem of a simple network fault diagnostic system is simulated, the results of simulation show that the improved approach can solve the problem of convergence better. |
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| Keywords: | expert system knowledge acquisition fault diagnosis genetic algorithm |
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