不确定信息的度量及其在制造中的应用示例

摘要/Abstract

摘要： 随机数学和模糊数学是描述不确定性现象的两种主要数学方法。申农用概率论作为度量信息的数学工具，把信息与不确定性关联起来；但申农熵只是一种概率熵，没有考虑其他型式的不确定性以及信息的含义与价值等。为此，对模糊不确定性的度量、复合熵和全信息作进一步陈述，探讨了信息熵在制造中的应用，并给出两个实例，其中一例是有关不确定切削力的复合熵计算，另一例是基于信息熵的加工过程自适应控制。

关键词: 信息测度, 不确定性, 概率熵, 模糊熵, 复合熵

Abstract: Probability and fuzzy logic were two main mathematical disciplines to address uncertainty. Shannon used probability as a mathematical tool to measure information, and associated information with uncertainty. Shannon’s entropy was just probabilistic entropy, but it didn’t take other kinds of uncertainties, meaning and value of information into consideration. So, measures of fuzzy uncertainty, composite entropy and comprehensive information were further described. Applications of information entropy in manufacturing were investigated and two examples were presented, one of which was about the composite entropy calculation for an uncertain cutting force, and the other was on information-entropy-based adaptive control of machining.

Key words: information measure, uncertainty, probabilistic entropy, fuzzy entropy, composite entropy

中图分类号:

O236

姚锡凡，张毅，董绍强，姚小群. 不确定信息的度量及其在制造中的应用示例[J]. .

YAO Xi-fan, ZHANG Yi, DONG Shao-qiang, YAO Xiao-qun. Measures of uncertain information and application cases in manufacturing[J]. .

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