Designing And Implementing The Fuzzy Extension Matrix System

The rule based expert system, which regarded the extension matrix as a powerful tool to study the computational complexity of learning from examples and to design learning algorithms. The main advantage of extension matrix induction is suitable for learning problems with high accuracy. This paper proposes a now approach to fuzzy rule generation from a set of examples with fuzzy representation. The new approach called fuzzy extension matrix incorporates the fuzzy entropy to search for paths and generalizes the concept of crisp extension matrix. This paper discussed the path of extension matrix and introduced a new heuristic algorithm. Using the path of extension matrix to represent the rule for the first in the algorithm. Therefore, the problem of fuzzy rule extraction can be converted into a search for paths of an extension matrix. Compared with the crisp extension matrix, the proposed method has the capability of handling fuzzy representation and tolerating noisy data or missing data.