A fuzzy-based pronostic adaptive system

Journal Europeen des Systemes Automatises

Volumn 30, Issue 2-3, 1996, Pages 281-299

  Frélicot, Carl ^a  

^a UNIVERSITÉ DE LA ROCHELLE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0000608898     PISSN: 12696935     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (18)

1. [BEZD 81] Bezdek J.C., Pattern recognition with fuzzy objective function algorithms, Plenum Press, 1981.
2. [BEZD 92] Bezdek J.C., Pal S.K., editors, Fuzzy models for pattern recognition, I.E.E.E. Press, 1992.
3. [CHOW 70] Chow C.K., An optimum recognition error and reject tradeoff, I.E.E.E. Trans. on Information Theory, IT-13, 41-46, 1970.
4. [DUB0 88] Dubois D., Prade H., Possibility theory - An approach to computerized processing of uncertainty, Plenum Press, 1988.
5. [DUBU 90] Dubuisson B., Diagnosis and pattern recognition, in french, Hermès, 1990.
6. [DUBU 93] Dubuisson B., Masson M.H., A statistical decision rule with incomplete knowledge about classes, Pattern Recognition, 26, 155-165, 1993.
7. [FREL 92] Frélicot C., Dubuisson B., K-step ahead prediction in the fuzzy decision space Application to prognosis, in Proc. of I.E.E.E. International Conference on Fuzzy Systems, San Diego, CA, 1992.
8. [FREL 93a] Frélicot C., Dubuisson B., A posteriori ambiguity reject solving in fuzzy pattern classification using a multi-step predictor of membership vectors, in Uncertainty in Intelligent Systems, ed. by B. Bouchon-Meunier, L. Valverde and R.R. Yager, Elsevier Science, 1993.
9. [FREL 93b] Frélicot C., Dubuisson B., An adaptive predictive diagnostic system based on fuzzy pattern recognition, in Proc. of IFAC World Congress, Sydney, NSW, Australia, 1993.
10. [ISER 84] Isermann R., Process fault detection based on modelling and estimation methods A survey, Automatica, 20, 387-404, 1984.
11. [JAIN 88] Jain A.K., Dubes R.C., Algorithms for clustering data, Prentice-Hall, 1988.
12. [MYER 76] Myers K.A., Tapley B.D., Adaptive sequential estimation with unknown noise statistics, I.E.E.E. Trans. on Automatic Control, AC-21, 520-523, 1976.
13. [PAL 91] Pal S.K., Fuzzy tools in the management of uncertainty in pattern recognition, image analysis, vision and expert systems, International Journal of Systems Sciences, 22, 511-549, 1991.
14. [PATT 89] Patton R.J., Frank P.M., Clark R.N., editors, Fault diagnosis in dynamic systems, Prentice-Hall, 1989.
15. [PATT 91] Patton R.J., Chen J., A review of parity space approaches to fault diagnosis, in Proc. of IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Baden-Baden, Germany, 1991.
16. [PEDR 90] Pedrycz W., Fuzzy sets in pattern recognition - methodology and methods. Pattern Recognition Letters, 23, 121-146, 1990.
17. [ROUB 82] Reubens M., Fuzzy clustering algorithms and their cluster validity, European Journal of Operational Research, 10, 294-301, 1982.
18. [ZADE 65] Zadeh L.A., Fuzzy sets, Information and Control, 8, 338-353, 1965.