Neurofuzzy inference system for stage classified of diabetes

Author

Gupta, Neeraj K. ; Tyagi, Neeraj

Author_Institution

Dept. of Electr. & Electron. Eng., Krishna Inst. of Eng. & Tech., Ghaziabad, India

fYear

2014

fDate

21-22 Feb. 2014

Firstpage

1265

Lastpage

1269

Abstract

In this paper, adaptive neurofuzzy inference system(ANFIS) approaches for automatically classified the diabetes is presented. ANFIS, used fuzzy logic expert system for decision making ability and neural network learning approach of backpropagation algorithm. Simulated result shows, the proposed work is effectively working with accuracy to classified the diabetes of reducing error rate with .0524.

Keywords

backpropagation; diseases; fuzzy logic; fuzzy neural nets; fuzzy set theory; inference mechanisms; medical diagnostic computing; ANFIS; adaptive neurofuzzy inference system; backpropagation algorithm; decision making; diabetes; fuzzy logic expert system; neural network learning approach; Conferences; Decision support systems; Handheld computers; Adaptive Neuro Fuzzy Inference System (ANFIS); Backpropagation; Diabetes; Fuzzy Logic;

fLanguage

English

Publisher

ieee

Conference_Titel

Advance Computing Conference (IACC), 2014 IEEE International

Conference_Location

Gurgaon

Print_ISBN

978-1-4799-2571-1

Type

conf

DOI

10.1109/IAdCC.2014.6779509

Filename

6779509

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=120922