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Volumn , Issue , 2014, Pages 85-93

E2GK-pro: An evidential evolving multimodeling approach for systems behavior prediction

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMICAL SYSTEMS; NONLINEAR DYNAMICAL SYSTEMS; UNCERTAINTY ANALYSIS;

EID: 84920541184     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (2)

References (16)
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    • (2008) Fuzzy Sets and Systems , pp. 3160-3182
    • Angelov, P.1    Lughofer, E.2    Zhou, X.3
  • 2
    • 0742272554 scopus 로고    scopus 로고
    • An approach to online identification of Takagi-Sugeno fuzzy models
    • Angelov, P. P., & Filev, D. P. (2004). An approach to online identification of Takagi-Sugeno fuzzy models. IEEE Trans Syst Man Cybern B Cybern, 34, 484-98.
    • (2004) IEEE Trans Syst Man Cybern B Cybern , vol.34 , pp. 484-498
    • Angelov, P.P.1    Filev, D.P.2
  • 3
    • 33644864393 scopus 로고    scopus 로고
    • On the plausibility transformation method for translating belief function models to probability models
    • Cobb, B. R., & Shenoy, P. P. (2006). On the plausibility transformation method for translating belief function models to probability models. International Journal of Approximate Reasoning, 41, 314-330.
    • (2006) International Journal of Approximate Reasoning , vol.41 , pp. 314-330
    • Cobb, B.R.1    Shenoy, P.P.2
  • 5
    • 79551492286 scopus 로고    scopus 로고
    • Reducing arbitrary choices in model building for prognostics: An approach by applying parsimony principle on an evolving neuro-fuzzy system
    • El-Koujok, M., Gouriveau, R., & Zerhouni, N. (2011). Reducing arbitrary choices in model building for prognostics: An approach by applying parsimony principle on an evolving neuro-fuzzy system. Microelectronics Reliability, 51, 310-330.
    • (2011) Microelectronics Reliability , vol.51 , pp. 310-330
    • El-Koujok, M.1    Gouriveau, R.2    Zerhouni, N.3
  • 8
    • 25144473310 scopus 로고    scopus 로고
    • Non linear process identification using a neural network based multiple models generator
    • Madani, K., Rybnik, M., & Chebira, A. (2003). Non Linear Process Identification Using a Neural Network Based Multiple Models Generator. LNCS series, 647-654.
    • (2003) LNCS Series , pp. 647-654
    • Madani, K.1    Rybnik, M.2    Chebira, A.3
  • 9
    • 36749023291 scopus 로고    scopus 로고
    • ECM: An evidential version of the fuzzy c-means algorithm
    • Masson, M.-H., & Denoeux, T. (2008). ECM: An evidential version of the fuzzy c-means algorithm. Pattern Recognition, 41(4), 1384-1397.
    • (2008) Pattern Recognition , vol.41 , Issue.4 , pp. 1384-1397
    • Masson, M.-H.1    Denoeux, T.2
  • 10
    • 0033280085 scopus 로고    scopus 로고
    • Regression analysis using fuzzy evidence theory
    • Petit-Renaud, S., & Denoeux, T. (1999). Regression analysis using fuzzy evidence theory. Proceedings of FUZZ-IEEE, 3, 1229-1234.
    • (1999) Proceedings of FUZZ-IEEE , vol.3 , pp. 1229-1234
    • Petit-Renaud, S.1    Denoeux, T.2
  • 11
    • 33847205037 scopus 로고    scopus 로고
    • A Multi-Modeling Strategy based on Belief Function Theory
    • Ramdani, M., Mourot, G., & Ragot, J. (2005). A Multi-Modeling Strategy based on Belief Function Theory. In CDC-ECC '05.
    • (2005) CDC-ECC '05
    • Ramdani, M.1    Mourot, G.2    Ragot, J.3
  • 14
    • 0028406490 scopus 로고
    • The transferable belief model
    • Smets, P., & Kennes, R. (1994). The Transferable Belief Model. Artificial Intelligence, 66, 191-234.
    • (1994) Artificial Intelligence , vol.66 , pp. 191-234
    • Smets, P.1    Kennes, R.2
  • 15
    • 0021892282 scopus 로고
    • Fuzzy identification of systems and its application to modeling and control
    • Takagi, T., & Sugeno, M. (1985). Fuzzy identification of systems and its application to modeling and control. IEEE Trans. On Systems Man and Cyberneticc, 15, 116-132.
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    • Takagi, T.1    Sugeno, M.2
  • 16
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    • Including probabilistic uncertainty in fuzzy logic controller modeling using Dempster-Shafer theory
    • Yager, R. R., & Filev, D. P. . (1995). Including probabilistic uncertainty in fuzzy logic controller modeling using Dempster-Shafer theory. IEEE Trans. Syst., Man, Cybern., 25, 1221-1230.
    • (1995) IEEE Trans. Syst., Man, Cybern , vol.25 , pp. 1221-1230
    • Yager, R.R.1    Filev, D.P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.