| 引用本文: | 张雪江 ， 朱向阳， 钟秉林， 黄 仁.基于退火演化算法的知识获取机制的研究*[J].控制理论与应用,1998,15(1):93~99.[点击复制] |
| ZHANG Xuejiang, ZHU Xiangyang, ZHONG Binglin and HUANG Ren.Research on Annealing-Genetic Algorithm Based Knowledge Acquisition[J].Control Theory and Technology,1998,15(1):93~99.[点击复制] |
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| 基于退火演化算法的知识获取机制的研究* |
| Research on Annealing-Genetic Algorithm Based Knowledge Acquisition |
| 摘要点击 711 全文点击 386 投稿时间：1996-06-03 修订日期：1997-03-04 |
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| DOI编号 |
| 1998,15(1):93-99 |
| 中文关键词 知识获取 组合优化 退火演化算法 |
| 英文关键词 knowledge acquisition combinatorial optimization annealing-genetic algorithm |
| 基金项目 |
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| 中文摘要 |
| 针对专家系统知识获取的“瓶颈”问题， 本文从优化角度建立了一个最终可被归结为大规模组合优化问题的知识获取模型， 并通过基因遗传算法和模拟退火算法结合后所构成的退火演化算法求解该模型， 从而实现知识库的自动生成. |
| 英文摘要 |
| Knowledge acquisition is a “bottleneck” for building expert system.ln this paper,a realvalued criterion is proposed to evaluate the performance of the rule. On this basis,knowledge acquisition is reduced to a large-scale combinatorial optimization problem. A hybrid approach with the genetic algorithm being em- bedded in simulated annealing,which is defined as annealing-genetic algorithm,is proposed to solve the prob- lem. By this strategy,the knowledge base can be automatically generated from examples. |
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