Fuzzy model validation using the local statistical approach Export

@article{citeulike:3909849, abstract = {The local statistical approach for fault detection and isolation is applied to fuzzy models validation. The method detects the inconsistencies between a fuzzy rule base and the modelled system. It can also identify which are the faulty parameters of the fuzzy model. The Fisher information matrix explains the detectability of changes in the parameters of the fuzzy model. Simulation tests illustrate the method's credibility.}, author = {Rigatos, G. and Zhang, Q.}, citeulike-article-id = {3909849}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.fss.2008.07.008}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0165011408003412}, day = {24}, doi = {10.1016/j.fss.2008.07.008}, issn = {01650114}, journal = {Fuzzy Sets and Systems}, keywords = {fuzzy, model, statistical, validation}, month = {July}, posted-at = {2009-01-20 04:20:42}, priority = {2}, title = {Fuzzy model validation using the local statistical approach}, url = {http://dx.doi.org/10.1016/j.fss.2008.07.008}, year = {2008} }

TY - JOUR ID - citeulike:3909849 L3 - citeulike-article-id:3909849 N2 - The local statistical approach for fault detection and isolation is applied to fuzzy models validation. The method detects the inconsistencies between a fuzzy rule base and the modelled system. It can also identify which are the faulty parameters of the fuzzy model. The Fisher information matrix explains the detectability of changes in the parameters of the fuzzy model. Simulation tests illustrate the method's credibility. JF - Fuzzy Sets and Systems SN - 01650114 TI - Fuzzy model validation using the local statistical approach KW - fuzzy KW - model KW - statistical KW - validation AU - Rigatos, G AU - Zhang, Q PY - 2008/07/24/ UR - http://dx.doi.org/10.1016/j.fss.2008.07.008 ER -