@article {1838,
	title = {A TSK-Type Recurrent Neuro-Fuzzy Systems for Fault Prognosis, ISSN/ISBN: 1945-3116/1945-3124.},
	journal = { Journal of Software Engineering and Applications (JESA)},
	volume = {58},
	number = {07},
	year = {2012},
	pages = {449-458},
	abstract = {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.},
	url = {https://file.scirp.org/Html/5-9301363_19730.htm},
	author = {Mahdaoui Rafik and Mouss Leila Hayet}
}
