| 基于退火演化算法的知识获取机制的研究* |
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| 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. |
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| 作者姓名： | 张雪江 朱向阳 钟秉林 黄 仁 |
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| 作者单位： | 东南大学机械工程系!南京，210096 |
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| 基金项目： | 国家自然科学基金!59275240，江苏省应用基础基金!BJ95030 |
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| 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。
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| 关 键 词： | 知识获取 专家系统 机器学习 退火演化算法 |
| 收稿时间： | 6/3/1996 12:00:00 AM |
| 修稿时间： | 3/4/1997 12:00:00 AM |
Research on Annealing-Genetic Algorithm Based Knowledge Acquisition |
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| ZHANG Xuejiang,ZHU Xiangyang,ZHONG Binglin and HUANG Ren.Research on Annealing-Genetic Algorithm Based Knowledge Acquisition[J].Control Theory & Applications,1998,15(1):93-99. |
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| Authors: | ZHANG Xuejiang ZHU Xiangyang ZHONG Binglin and HUANG Ren |
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| Abstract: | Knowledge acquisition is a "bottleneck" for building expert system. In 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 embedded in simulated annealing,which is defined as annealing-genetic algorithm,is proposed to solve the problem. By this strategy,the knowledge base can be automatically generated from examples. |
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| Keywords: | knowledge acquisition combinatorial optimization annealing-genetic algorithm |
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