基于平均压缩熵的疲劳损伤钢桥改造方法选择

Masaru Minagawa, T. Kamitani
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引用次数: 0

摘要

[摘要]为了知识发现的目的,我们使用我们提出的推理系统来评估通过一些推理虚拟构建的案例库的平均压缩熵,以选择改进方法。分析发现,平均压缩熵是发现隐含在数据库或案例库中的知识的有效度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Knowledge Discovery using Average Compressed Entropy for selecting retrofitting Method of Steel Bridges Damaged by Fatigue
[ABSTRACT] For the purpose of knowledge discovery, we evaluated average compressed entropies for a case-base virtually constructed through some inferences with the inference system that we proposed for selecting the retrofitting method. It is found from the analyses that the average compressed entropy is an effective measure for the discovery of knowledge that is implicitly buried into dada-bases or case-bases.
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