Fuzzy modelling and identification with genetic algorithm based learning - Wu, Baolin; Yu, Xinghuo (Fuzzy sets and systems, 2000)
A GA based learning algorithm is proposed in this paper for the identification of TSK models. The algorithm consists of four blocks: Partition Block, GA Block, Tuning Block and Termination Block. The Partition Block is to determine an estimated partition of input variables. The GA Block is to optimise the structure of a TSK model. The Tuning Block is to fine tune the parameters of the TSK model using the gradient descent based approach and the Termination Block checks that the resultant TSK model is satisfactory. The proposed GABL algorithm has the advantage of simplicity, flexibility, high accuracy and automation. The presented numerical examples indicate that the GABL algorithm is effective in constructing a good TSK model for complex nonlinear systems.