ABSTRACT

Fuzzy classification rules are widely considered as a wellsuited representation of classification knowledge, as they allow readable and interpretable rule bases. The goal of this paper is to discuss how fuzzy classification rules are generated for soil data. The most important task in the design of fuzzy classification systems is to find a set of fuzzy rules from training data to deal with a specific classification problem. In this paper, we generate fuzzy rules from training data to deal the soil data classification problem, by first defining the membership functions for the input attributes of the soil data, and then generating the initial fuzzy rules for the training data based on the member functions defined for the attributes of the soil data and then we merge these fuzzy rules in order to generate definitive fuzzy rules .