<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mahdaoui Rafik</style></author><author><style face="normal" font="default" size="100%">Mouss Leila Hayet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A TSK-Type Recurrent Neuro-Fuzzy Systems for Fault Prognosis, ISSN/ISBN: 1945-3116/1945-3124.</style></title><secondary-title><style face="normal" font="default" size="100%"> Journal of Software Engineering and Applications (JESA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://file.scirp.org/Html/5-9301363_19730.htm</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">449-458</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">As a result from the demanding of process safety, reliability and environmental constraints, a called of fault detection and diagnosis system become more and more important. In this article some basic aspects of TSK (Takigi Sugeno Kang) neuro-fuzzy techniques for the prognosis and diagnosis of manufacturing systems are presented. In particular, a neuro-fuzzy model that can be used for the identification and the simulation of faults prognosis models is described. The presented model is motivated by a cooperative neuro-fuzzy approach based on a vectorized recurrent neural network architecture. The neuro-fuzzy architecture maps the residuals into two classes: a one of fixed direction residuals and another one of faults belonging to rotary kiln.</style></abstract><issue><style face="normal" font="default" size="100%">07</style></issue></record></records></xml>