id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_glaaka4gpve2bihl6su7kfhsq4	U. Mohan Rao	Subtractive Clustering Fuzzy Expert System for Engineering Applications	2015	7	.pdf	application/pdf	2710	285	60	Performance of a fuzzy expert system is related with how good the membership functions are normalized, tuned for a problem that are best suited for the problem statement by integrating subtractive clustering method for fuzzy expert system design. Subtractive clustering algorithm is used to generate the tuned membership functions automatically in accordance to the domain The proposed integrated design of clustering based fuzzy expert system acts in improving the accuracy and leads to a which acts in proposing a novel alternative designing ideology for integrated fuzzy clustering expert system in After applying the subtractive clustering algorithm an inference engine with the tuned membership functions will input and output files were initiated and radius value declared apply subtractive clustering algorithm the function for environment.The inference engine IE-2 obtained from subtractive clustering algorithm has its membership functions In this case fuzzy inference engine is generated with three input membership functions which 	./cache/work_glaaka4gpve2bihl6su7kfhsq4.pdf	./txt/work_glaaka4gpve2bihl6su7kfhsq4.txt