| 摘要: |
| 本文为解决知识系统构造过程中的瓶颈问题──知识获取，提出了一种基于神经网络ＮＮ（ｎｅｕｒａｌｎｅｔｗｏｒｋ）的自动获取多级推理产生式规则的Ｎ－Ｒ方法，该方法采用了特有的ＮＮ结构模型和相应的学习算法，使得ＮＮ在学习过程中动态确定隐层节点数的同时，也产生了样例集中没有定义的新概念，学习后的ＮＮ能用本文提出的转换算法转换成推理网络，最终方便地得到产生式规则集. |
| 关键词: 知识获取 机器学习 神经网络 产生式系统 推理 |
| DOI： |
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| 基金项目:本文研究得到国家自然科学基金资助. |
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| THE N-R METHOD OF ACQUIRING KNOWLEDGE AUTOMATICALLY AND INTERACTIVELY BASED ON NEURAL NETWORK |
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Li Yi,Shi Hongbao
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| Abstract: |
| This paper presents a N-R method of acquiring multi-level reasoning production rules automatically based on NN(neural network), so as to resolve the bottle neckproblem in building a knowledge - based system-knowledge acquisition. This methodadopts a characteristic NN structure model and corresponding learning algorithm, so thatN -R method can fix the number of hidden nodes dynamically and form new conceptswhich are not defined in the sample set in the course of learning. Having been trained, NNis transformed into an RN (reasoning network) with the proposed transform algorithm,from which productionrules can be obtained easily. |
| Key words: Knowledge acquisition machine learning neural network production system inference. |
