메뉴 건너뛰기




Volumn 141, Issue 1, 2004, Pages 33-46

A fast genetic method for inducting descriptive fuzzy models

Author keywords

Backfitting; Boosting algorithms; Descriptive fuzzy models; Genetic fuzzy systems; Matching pursuit

Indexed keywords

APPROXIMATION THEORY; GENETIC ALGORITHMS; KNOWLEDGE BASED SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; LINGUISTICS; MATHEMATICAL MODELS; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS;

EID: 0347622658     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(03)00112-X     Document Type: Conference Paper
Times cited : (14)

References (27)
  • 2
    • 0012890352 scopus 로고    scopus 로고
    • Finding a balance between interpretability and accuracy in fuzzy rule-based modeling: An overview
    • J. Casillas, O. Cordón, F. Herrera, & L. Magdalena. Physica-Verlag. to appear
    • Casillas J., Cordón O., Herrera F., Magdalena L. Finding a balance between interpretability and accuracy in fuzzy rule-based modeling: an overview. Casillas J., Cordón O., Herrera F., Magdalena L. Trade-Off Between Accuracy and Interpretability in Fuzzy Rule-Based Modeling. 2002;Physica-Verlag. to appear.
    • (2002) Trade-off between Accuracy and Interpretability in Fuzzy Rule-based Modeling
    • Casillas, J.1    Cordón, O.2    Herrera, F.3    Magdalena, L.4
  • 3
    • 0034387057 scopus 로고    scopus 로고
    • Novel fuzzy logic control based on weighting of partially inconsistent rules using neural network
    • Cho J.S., Park D.J. Novel fuzzy logic control based on weighting of partially inconsistent rules using neural network. J. Intell. Fuzzy Systems. 8:2000;99-110.
    • (2000) J. Intell. Fuzzy Systems , vol.8 , pp. 99-110
    • Cho, J.S.1    Park, D.J.2
  • 4
    • 0031268161 scopus 로고    scopus 로고
    • A three-stage evolutionary process for learning descriptive and approximative fuzzy logic controller knowledge bases from examples
    • Cordón O., Herrera F. A three-stage evolutionary process for learning descriptive and approximative fuzzy logic controller knowledge bases from examples. Int. J. Approx. Reason. 17(1):1997;369-407.
    • (1997) Int. J. Approx. Reason. , vol.17 , Issue.1 , pp. 369-407
    • Cordón, O.1    Herrera, F.2
  • 5
    • 0034207436 scopus 로고    scopus 로고
    • A proposal for improving the accuracy of linguistic modeling
    • Cordón O., Herrera F. A proposal for improving the accuracy of linguistic modeling. IEEE Trans. Fuzzy Syst. 8(3):2000;335-344.
    • (2000) IEEE Trans. Fuzzy Syst. , vol.8 , Issue.3 , pp. 335-344
    • Cordón, O.1    Herrera, F.2
  • 6
    • 0031077287 scopus 로고    scopus 로고
    • Applicability of the fuzzy operators in the design of fuzzy logic controllers
    • Cordón O., Herrera F., Peregrin A. Applicability of the fuzzy operators in the design of fuzzy logic controllers. Fuzzy Sets and Systems. 86:1997;15-41.
    • (1997) Fuzzy Sets and Systems , vol.86 , pp. 15-41
    • Cordón, O.1    Herrera, F.2    Peregrin, A.3
  • 8
    • 0000259511 scopus 로고    scopus 로고
    • Approximate statistical tests for comparing supervised classification learning algorithms
    • Dietterich G. Approximate statistical tests for comparing supervised classification learning algorithms. Neural Comput. 10(7):1998;1895-1924.
    • (1998) Neural Comput. , vol.10 , Issue.7 , pp. 1895-1924
    • Dietterich, G.1
  • 9
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • Friedman J., Hastie T., Tibshirani R. Additive logistic regression. a statistical view of boosting Ann. Statist. 28(2):2000;337-374.
    • (2000) Ann. Statist. , vol.28 , Issue.2 , pp. 337-374
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 10
    • 0032069167 scopus 로고    scopus 로고
    • Completeness and consistency conditions for learning fuzzy rules
    • Gonzalez A., Perez R. Completeness and consistency conditions for learning fuzzy rules. Fuzzy Sets and Systems. 96:1996;37-51.
    • (1996) Fuzzy Sets and Systems , vol.96 , pp. 37-51
    • Gonzalez, A.1    Perez, R.2
  • 12
    • 0348215352 scopus 로고    scopus 로고
    • Boosting a fenetic fuzzy classifier
    • Vancouver, Canada
    • F. Hoffmann, Boosting a fenetic fuzzy classifier, Proc. IFSA 2001, Vancouver, Canada, 2001.
    • (2001) Proc. IFSA 2001
    • Hoffmann, F.1
  • 13
    • 0002131213 scopus 로고    scopus 로고
    • Using the Adaboost algorithm to induce fuzzy rules in classification problems
    • Sevilla
    • L. Junco, L. Sanchez, Using the Adaboost algorithm to induce fuzzy rules in classification problems, Proc. ESTYLF 2000, Sevilla, 2001, pp. 297-301.
    • (2001) Proc. ESTYLF 2000 , pp. 297-301
    • Junco, L.1    Sanchez, L.2
  • 14
    • 0027842081 scopus 로고
    • Matching pursuits with time-frequency dictionaries
    • Mallat S., Zhang Z. Matching pursuits with time-frequency dictionaries. IEEE Trans. Signal Process. 41:1993;3397-3415.
    • (1993) IEEE Trans. Signal Process. , vol.41 , pp. 3397-3415
    • Mallat, S.1    Zhang, Z.2
  • 15
    • 0000864293 scopus 로고    scopus 로고
    • A simple but powerful heuristic method for generating fuzzy rules from numerical data
    • Nozaki K., Ishibuchi H., Tanaka H. A simple but powerful heuristic method for generating fuzzy rules from numerical data. Fuzzy Sets and Systems. 86:1997;251-270.
    • (1997) Fuzzy Sets and Systems , vol.86 , pp. 251-270
    • Nozaki, K.1    Ishibuchi, H.2    Tanaka, H.3
  • 16
    • 0033416388 scopus 로고    scopus 로고
    • Handling of inconsistent rules with an extended model of fuzzy reasoning
    • Pal N.R., Pal K. Handling of inconsistent rules with an extended model of fuzzy reasoning. J. Intelligent and Fuzzy Systems. 7:1998;55-73.
    • (1998) J. Intelligent and Fuzzy Systems , vol.7 , pp. 55-73
    • Pal, N.R.1    Pal, K.2
  • 17
    • 0004114283 scopus 로고
    • PROBEN1-A set of benchmarks and benchmarking rules for neural network training algorithms
    • Fakultät für Informatik, Universität Karlsruhe
    • L. Prechelt, PROBEN1-A set of benchmarks and benchmarking rules for neural network training algorithms, Technical Report 21/94, Fakultät für Informatik, Universität Karlsruhe, 1994.
    • (1994) Technical Report , vol.21
    • Prechelt, L.1
  • 18
    • 0033740103 scopus 로고    scopus 로고
    • Interval-valued GA-P algorithms
    • Sánchez L. Interval-valued GA-P algorithms. IEEE Trans. Evol. Comput. 4(1):2000;64-72.
    • (2000) IEEE Trans. Evol. Comput. , vol.4 , Issue.1 , pp. 64-72
    • Sánchez, L.1
  • 20
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • Schapire R.E. The strength of weak learnability. Mach. Learning. 5(2):1990;197-227.
    • (1990) Mach. Learning , vol.5 , Issue.2 , pp. 197-227
    • Schapire, R.E.1
  • 21
    • 0001227575 scopus 로고
    • Additive regression and other nonparametric models
    • Stone C.J. Additive regression and other nonparametric models. Ann. Statist. 13:1985;689-705.
    • (1985) Ann. Statist. , vol.13 , pp. 689-705
    • Stone, C.J.1
  • 22
    • 0027544110 scopus 로고
    • A fuzzy-logic-based approach to qualitative modeling
    • Sugeno N., Yasukawa T. A fuzzy-logic-based approach to qualitative modeling. IEEE Trans. Fuzzy Systems. 1(1):1993;7-31.
    • (1993) IEEE Trans. Fuzzy Systems , vol.1 , Issue.1 , pp. 7-31
    • Sugeno, N.1    Yasukawa, T.2
  • 23
    • 0036643065 scopus 로고    scopus 로고
    • Kernel matching pursuit
    • Vincent P., Bengio Y. Kernel matching pursuit. Mach. Learning. 48:2002;165-187.
    • (2002) Mach. Learning , vol.48 , pp. 165-187
    • Vincent, P.1    Bengio, Y.2
  • 24
    • 0000769851 scopus 로고
    • Generating fuzzy rules by learning from examples
    • Wang L.X., Mendel J. Generating fuzzy rules by learning from examples. IEEE Trans. Syst. Man Cybernet. 25(2):1992;353-361.
    • (1992) IEEE Trans. Syst. Man Cybernet. , vol.25 , Issue.2 , pp. 353-361
    • Wang, L.X.1    Mendel, J.2
  • 25
    • 84974751468 scopus 로고
    • Design of fuzzy logic controller with inconsistent rule base
    • Yu W., Bien Z. Design of fuzzy logic controller with inconsistent rule base. J. Intelligent Fuzzy Systems. 2:1994;147-159.
    • (1994) J. Intelligent Fuzzy Systems , vol.2 , pp. 147-159
    • Yu, W.1    Bien, Z.2
  • 26
    • 0002263693 scopus 로고
    • Fuzzy sets and information granularity
    • M.M. Gupta, R.K. Ragade, & R.R. Yager. New York: North-Holland
    • Zadeh L.A. Fuzzy sets and information granularity. Gupta M.M., Ragade R.K., Yager R.R. Advances in Fuzzy Set Theory and Applications. 1979;3-18 North-Holland, New York.
    • (1979) Advances in Fuzzy Set Theory and Applications , pp. 3-18
    • Zadeh, L.A.1
  • 27
    • 84898974832 scopus 로고    scopus 로고
    • Kernel logistic regression and the import vector machine
    • T.G. Dietterich, S. Becker, & Z. Ghahramani. Cambridge, MA: MIT Press
    • Zhu J., Hastie T. Kernel logistic regression and the import vector machine. Dietterich T.G., Becker S., Ghahramani Z. Advances in Neural Information Processing Systems 14. 2002;1081-1088 MIT Press, Cambridge, MA.
    • (2002) Advances in Neural Information Processing Systems , vol.14 , pp. 1081-1088
    • Zhu, J.1    Hastie, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.