  In this paper, we propose a new fuzzy reasoning principle, so called Movement
and Transformation Principle(MTP). This Principle is to obtain a new fuzzy
reasoning result by Movement and Transformation the consequent fuzzy set in
response to the Movement, Transformation, and Movement-Transformation
operations between the antecedent fuzzy set and fuzzificated observation
information. And then we presented fuzzy modus ponens and fuzzy modus tollens
based on MTP. We compare proposed method with Mamdani fuzzy system, Sugeno
fuzzy system, Wang distance type fuzzy reasoning method and Hellendoorn
functional type method. And then we applied to the learning experiments of the
fuzzy neural network based on MTP and compared it with the Sugeno method.
Through prediction experiments of fuzzy neural network on the precipitation
data and security situation data, learning accuracy and time performance are
clearly improved. Consequently we show that our method based on MTP is
computationally simple and does not involve nonlinear operations, so it is easy
to handle mathematically.
