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Volumn , Issue , 2009, Pages

Diagnosis of diabetes by using adaptive neuro fuzzy inference systems

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; BINARY LOGIC; DEPENDENT VARIABLES; FUZZY INPUT; MULTINOMIAL LOGISTIC REGRESSION;

EID: 77950506823     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSCCW.2009.5379497     Document Type: Conference Paper
Times cited : (12)

References (11)
  • 1
    • 34249285900 scopus 로고    scopus 로고
    • An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease
    • Polat K, Günes S: An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease. ELSEVIER, Digital Signal Processing 17 (2007) 702-710
    • (2007) ELSEVIER, Digital Signal Processing , vol.17 , pp. 702-710
    • Polat, K.1    Günes, S.2
  • 2
    • 33644654593 scopus 로고    scopus 로고
    • AMRAPALIKA: An expert system for the diagnosis ofpests, diseases, and disorders in Indian mango
    • R. Prasad, K. R. Ranjan, A.K. Sinha, "AMRAPALIKA: An expert system for the diagnosis ofpests, diseases, and disorders in Indian mango", Elsevier, Knowledge-Based Systems 19 (2006) 9-12
    • (2006) Elsevier, Knowledge-Based Systems , vol.19 , pp. 9-12
    • Prasad, R.1    Ranjan, K.R.2    Sinha, A.K.3
  • 3
    • 0030764450 scopus 로고    scopus 로고
    • Prevalence ofcoronary heart disease risk factors among rural blacks: A community-based study
    • Willems JP, Saunders JT, DE Hunt, JB Schorling: Prevalence ofcoronary heart disease risk factors among rural blacks: A community-based study. Southern Medical Journal 90:814-820; 1997
    • (1997) Southern Medical Journal , vol.90 , pp. 814-820
    • Willems, J.P.1    Saunders, J.T.2    Hunt, D.E.3    Schorling, J.B.4
  • 6
    • 0003753097 scopus 로고    scopus 로고
    • Neuro- Fuzzy and soft computing. a computational approach to learning and machine intelligent
    • Prentice Hall International
    • Jang J. S. R., Sun C. T. and Mizutani E: "Neuro- fuzzy and soft computing. A computational approach to learning and machine intelligent". United States of America. Prentice Hall International; 1997.
    • (1997) United States of America
    • Jang, J.S.R.1    Sun, C.T.2    Mizutani, E.3
  • 7
    • 45449126257 scopus 로고
    • Sturcture identification of fuzzy model
    • SUGENO, M., KANG, G.T., Sturcture identification of fuzzy model. Fuzzy sets and Systems, 28(1988), pp.15-33.
    • (1988) Fuzzy Sets and Systems , vol.28 , pp. 15-33
    • Sugeno, M.1    Kang, G.T.2
  • 8
    • 0021892282 scopus 로고
    • Fuzzy identification of systems and its application to modeling and control
    • TAKAGI, T. and SUGENO, M., Fuzzy identification of systems and its application to modeling and control. IEEE Trans. On Systems, Man & Cybernetics, 15(1985), pp.116-132.
    • (1985) IEEE Trans. on Systems, Man & Cybernetics , vol.15 , pp. 116-132
    • Takagi, T.1    Sugeno, M.2
  • 9
    • 0016451032 scopus 로고
    • An experiment in linguistic synthesis with a fuzzy logic controller
    • MAMDANI, E. H. and ASSILIAN, S., An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1), (1975), pp.:1-13
    • (1975) International Journal of Man-Machine Studies , vol.7 , Issue.1 , pp. 1-13
    • Mamdani, E.H.1    Assilian, S.2
  • 10
    • 0002906650 scopus 로고
    • An approach to fuzzy reasoning method
    • M. M. Gupta, R. K.Ragade, and R. R. Yager, editors
    • TSUKAMATO, Y., An approach to fuzzy reasoning method. In M. M. Gupta, R. K.Ragade, and R. R. Yager, editors, Advances in Fuzzy Set Theory and Applications, (1979), pp:137-149.
    • (1979) Advances in Fuzzy Set Theory and Applications , pp. 137-149
    • Tsukamato, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.