Weighted Fuzzy Rule-Based System Combined With A Novel Simplified E.Coli Foraging Optimization Algorithm

A simplified E.Coli foraging optimization algorithm is presented in this paper, which simulates the chemo-tactic behavior of E.Coli. The optimization algorithm characterizes the easy implementation and the fact that no gradient information is required. The operators of the algorithm are described in details. The simplified E.Coli algorithm consists of a tumbling operator and a swimming operator. At the same time the optimal position of individual E.Coli and the location of all E.Coli swarm are adopted to update the locations of swarm. In this paper, a weighted fuzzy rule-based system has been designed, in which the parameters of membership functions including position and shape of the fuzzy rule set and weights of rules are estimated using the simplified E.Coli foraging optimization algorithm. The efficiency of the system has been illustrated in the process of classifying the iris data. This paper also shows that weighted fuzzy rules can lead to better fuzzy system compared with non-weighted fuzzy rules.