模糊推理:近似推理理论的另一种选择

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI:10.1109/ISUMA.1995.527741

W. Siler, J. Buckley

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引用次数: 4

摘要

模糊逻辑在模糊控制中的应用是非常普遍的。然而，对于更一般的模糊推理问题，有许多重要的思想必须解决。我们讨论了这些主题:(1)近似推理理论在模糊推理系统中的效用可能是可疑的:我们提出了不能用近似推理来评估的模糊规则的例子。(2)在模糊推理中，去模糊化是模糊化的逆，这是直观的。(3)在某些情况下，应遵循被排除的中间律;当andding或ORing不兼容时，可以通过切换到Lukasiewicz逻辑轻松实现这一点。(4)如果要进行多步推理，必须考虑数据置信度和离散模糊集隶属度等级的先验知识。(5)通用模糊推理系统应该是基于非模糊人工智能的推理系统的泛化，应该能够做到非模糊推理系统所能做到的事情。

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Fuzzy reasoning: an alternative to approximate reasoning theory

Applications of fuzzy logic to fuzzy control are very popular. However, for more general fuzzy reasoning problems, there are a number of important ideas that must be addressed. We discuss these topics: (1) The theory of approximate reasoning may be of dubious utility in fuzzy reasoning systems: we present examples of fuzzy rules which cannot be evaluated by approximate reasoning. (2) In fuzzy reasoning, it is intuitive that defuzzification be the inverse of fuzzification. (3) In some situations, the excluded middle law should be obeyed; this can be easily accomplished by switching to the Lukasiewicz logic when ANDing or ORing incompatible conditions. (4) Prior knowledge of confidences in data and of grades of membership of discrete fuzzy sets must be taken into account if multi-step reasoning is to be carried out. (5) A general-purpose fuzzy reasoning system should be a generalization of a non-fuzzy artificial intelligence based reasoning system, and should be able to do what nonfuzzy reasoning systems can do.

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Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society

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