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In this paper, we propose a new fuzzy reasoning principle, so called Movementand Transformation Principle(MTP). This Principle is to obtain a new fuzzyreasoning result by Movement and Transformation the consequent fuzzy set inresponse to the Movement, Transformation, and Movement-Transformationoperations between the antecedent fuzzy set and fuzzificated observationinformation. And then we presented fuzzy modus ponens and fuzzy modus tollensbased on MTP. We compare proposed method with Mamdani fuzzy system, Sugenofuzzy system, Wang distance type fuzzy reasoning method and Hellendoornfunctional type method. And then we applied to the learning experiments of thefuzzy neural network based on MTP and compared it with the Sugeno method.Through prediction experiments of fuzzy neural network on the precipitationdata and security situation data, learning accuracy and time performance areclearly improved. Consequently we show that our method based on MTP iscomputationally simple and does not involve nonlinear operations, so it is easyto handle mathematically.

New Movement and Transformation Principle of Fuzzy Reasoning and Its Application to Fuzzy Neural Network