Fuzzy system modeling using linear distance rules
An approach of determining significant variables for multi-input systems is proposed by using a modified fuzzy rule form, called linear distance rules (LDR). By defining an index, we can know the influences of input signals on output and can determine significant variables from the index. We also propose a simple three-layered generalized neural network to realize the LDRs. Furthermore, this approach can be extended to decompose a multi-input-multi-output (MIMO) system into several simpler multi-input-single-output (MISO) systems. (C) 1999 Elsevier Science B.V. All rights reserved.
neural networks fuzzy model