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Dynamic tuning of parameterized defuzzification methods applied to automatic control and diagnosis

机译:用于自动控制和诊断的参数化反模糊化方法的动态调整

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Tuning parameterized defuzzification methods by dynamically adjusting parameters values according to dynamic changes in the environment have proven successful in optimizing fuzzy systems. This paper illustrates the techniques involved by discussing examples of dynamically tuning of one type of parameterized defuzzification method, those based on the basic defuzzification distribution (BADD) method. An application of dynamic tuning of parameterized defuzzification in optimizing automatic control and diagnostic systems which use fuzzy reasoning underline the potential offered by this technique in coping with complex tasks.
机译:通过根据环境中的动态变化动态调整参数值来调整参数化的反模糊化方法已被证明可以成功地优化模糊系统。本文通过讨论动态调整一种类型的参数化反模糊化方法的示例(基于基本反模糊化分布(BADD)方法的示例)来说明所涉及的技术。参数化去模糊化的动态调整在优化使用模糊推理的自动控制和诊断系统中的应用突显了该技术提供的应对复杂任务的潜力。

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