Research Andapplication On Dynamic Fuzzy Predicate Logic Relationslearning Algorithm

Machine Learning is a key part of Artificial Intelligence. Relation learning is a novel method which aims at searching for the relations between learning tasks to find the corresponding learning rules. As Dynamic Fuzzy Predication Logic relation is one of the basic theories to solve the Dynamic Fuzzy relation problems, in this paper, in allusion to the Dynamic Fuzzy relation problems, we'll deal with the Relation learning problems by using the Dynamic Fuzzy Predication Logic.And the main achievements are as follows:(1) The basic concepts for Dynamic Fuzzy Matrix expression and operation property are proposed, including Dynamic Fuzzy Matrix multiplication and its properties.(2) We represent new technologies of Dynamic Fuzzy Predication Logic relation, which can solve learning problem in case of unknown information insufficiency.(3) A simple face recognition system is realized, and the learning ability of the system is improved by Dynamic Fuzzy Predication Logic relation learning algorithm.Through the research and experiment in this paper, the feasibility of handling the learning problem by using Dynamic Fuzzy Predication Logic relation is confirmed, and a good effect is achieved.