Generalized Fuzzy Logic with twofold fuzzy set: Learning through Neural Net and Application to Business Intelligence

P. V. Reddy
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引用次数: 4

Abstract

The fuzzy logic deals with incomplete, inconsistent, uncertain, vagueand undecided information with belief. Fuzzy logic with twofold fuzzy set will give more accuracy then single membership function. In this paper, fuzzy logic with twofold fuzzy sets are studied. Fuzzy neural net used learn fuzzy inference. Fuzz certainity factor (FCF) is studied to eliminate conflict between two membership functions. Sometimes decision has to be taken under risk. Fuzzy Decision set is defined with fuzzy certainty factor (FCF). Different fuzzy resoning methods are discussed. Fuzzy inference anr reasoning mrthods are given for business intelligence.
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双模糊集广义模糊逻辑:神经网络学习及其在商业智能中的应用
模糊逻辑用信念处理不完整、不一致、不确定、模糊和未确定的信息。具有双重模糊集的模糊逻辑比单一隶属函数具有更高的精度。本文研究了具有双重模糊集的模糊逻辑。采用模糊神经网络学习模糊推理。研究了模糊确定性因子(FCF)来消除两个隶属函数之间的冲突。有时候做决定要冒险。用模糊确定性因子(FCF)来定义模糊决策集。讨论了不同的模糊推理方法。给出了商业智能的模糊推理和推理方法。
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