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›› 2002, Vol. 28 ›› Issue (07): 21-.

• 论文 • 上一篇    下一篇

用神经网络来实现基于范例的推理系统

倪志伟,蔡庆生,贾瑞玉   

  1. 中国科学技术大学计算机系,中国科学技术大学计算机系,安徽大学计算智能与信号处理国家教育部重点实验室 合肥 230027;安徽大学计算智能与信号处理国家教育部重点实验室合肥 230039
  • 发布日期:2002-07-25

Building Case-based Reasoning System with Neural Networks

NI Zhiwei1,2,CAI Qingsheng 1,JJA Ruiyu2   

  1. (1. Department of Computer Science, University of Science and Technology of China, Hefei 2300272.The Key Laboratory of Intelligent Computing and Signal Processing ,Ministry of Education, Hefei 230039)
  • Published:2002-07-25

摘要: 范例推理与神经网络有一种自然的联系。神经网络有许多优点,利用神经网络来实现范例推理可以取得非常好的效果。文章首先详细探讨了在范例推理中使用的神经网络模型与技术,并给出了其上的搜索与学习算法以及数据挖掘算法,旨在提高范例推理系统的鲁棒性和知识获取的自动化程度。

关键词: 范例推理, 神经网络, IAC网络, 数据挖掘, 范例检索算法, 学习算法

Abstract: There is a natural relationship between case-based reasoning and neural network. This paper examines the possibility of using neural network as a method of building such case-based systems. Better results in CBR system could be achieved by using neural network. A simple efficient case-based system structure is constructed with neural network. Also, some algorithms are proposed and tested. The purpose of research is to heighten the robustness and automation of knowledge acquisition in case-based system. ;;;;;

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