메뉴 건너뛰기




Volumn 11, Issue 8, 2011, Pages 4847-4858

A rule-based symbiotic modified differential evolution for self-organizing neuro-fuzzy systems

Author keywords

Control; Differential evolution; Entropy measure; Neuro fuzzy systems; Symbiotic evolution

Indexed keywords

DIFFERENTIAL EVOLUTION; ENTROPY MEASURE; FUZZY PARTITION; INPUT VARIABLES; MODIFIED DIFFERENTIAL EVOLUTION; NEURO-FUZZY SYSTEMS; NEUROFUZZY SYSTEM; PARAMETER LEARNING; RULE BASED; SELF ORGANIZING; STRUCTURE-LEARNING; SYMBIOTIC EVOLUTION;

EID: 80053560237     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.06.015     Document Type: Article
Times cited : (13)

References (31)
  • 7
    • 0001268158 scopus 로고    scopus 로고
    • Evolving fuzzy rule based controllers using genetic algorithms
    • B. Carse, T.C. Fogarty, and A. Munro Evolving fuzzy rule based controllers using genetic algorithms Fuzzy Sets Syst. 80 June 1996 273 293 (Pubitemid 126667427)
    • (1996) Fuzzy Sets and Systems , vol.80 , Issue.3 , pp. 273-293
    • Carse, B.1    Fogarty, T.C.2    Munro, A.3
  • 8
    • 0001603936 scopus 로고
    • Tuning fuzzy logic controllers by genetic algorithms
    • APRIL-MAY
    • F. Herrera, M. Lozano, and J.L. Verdegay Tuning fuzzy logic controllers by genetic algorithms Int. J. Approx. Reas. 12 April-May 1995 299 315
    • (1995) Int. J. Approx. Reas. , vol.12 , pp. 299-315
    • Herrera, F.1    Lozano, M.2    Verdegay, J.L.3
  • 9
    • 0007911636 scopus 로고
    • Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms
    • A. Homaifar, and E. McCormick Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms IEEE Trans. Fuzzy Syst. 3 1995 May 129 139
    • (1995) IEEE Trans. Fuzzy Syst. , vol.3 , pp. 129-139
    • Homaifar, A.1    McCormick, E.2
  • 10
    • 0032188222 scopus 로고    scopus 로고
    • Genetic-based on-line learning for fuzzy process control
    • J. Velasco Genetic-based on-line learning for fuzzy process control Int. J. Intell. Syst. 13 1998 891 903 (Pubitemid 128608583)
    • (1998) International Journal of Intelligent Systems , vol.13 , Issue.10-11 , pp. 891-903
    • Velasco, J.R.1
  • 11
    • 0032597810 scopus 로고    scopus 로고
    • Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems
    • H. Ishibuchi, T. Nakashima, and T. Murata Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems IEEE Trans. Syst. Man Cybern. B: Cybern. 29 1999 601 608
    • (1999) IEEE Trans. Syst. Man Cybern. B: Cybern. , vol.29 , pp. 601-608
    • Ishibuchi, H.1    Nakashima, T.2    Murata, T.3
  • 12
    • 0033317446 scopus 로고    scopus 로고
    • MOGUL: A methodology to obtain genetic fuzzy rule-based systems under the iterative rule learning approach
    • DOI 10.1002/(SI CI)1098-11 1X(19991 1)14:11<11 23::AID-I NT4>3.0.CO;2-6
    • O. Cordon, M.J. del Jesus, F. Herrera, and M. Lozano MOGUL: A methodology to obtain genetic fuzzy rule-based systems under the iterative rule learning approach Int. J. Intell. Syst. 14 1999 1123 1153 (Pubitemid 30547150)
    • (1999) International Journal of Intelligent Systems , vol.14 , Issue.11 , pp. 1123-1153
    • Cordon, O.1    Del Jesus, M.J.2    Herrera, F.3    Lozano, M.4
  • 13
    • 0033116171 scopus 로고    scopus 로고
    • SLAVE: A genetic learning system based on an iterative approach
    • APRIL
    • A. Gonzalez, and R. Perez SLAVE: a genetic learning system based on an iterative approach IEEE Trans. Fuzzy Syst. 27 April 1999 176 191
    • (1999) IEEE Trans. Fuzzy Syst. , vol.27 , pp. 176-191
    • Gonzalez, A.1    Perez, R.2
  • 14
    • 0032142042 scopus 로고    scopus 로고
    • FuGeNeSys - A fuzzy genetic neural system for fuzzy modeling
    • PII S1063670698051534
    • M. Russo FuGeNeSys: a fuzzy genetic neural system for fuzzy modeling IEEE Trans. Fuzzy Syst. 6 1998 373 388 (Pubitemid 128750069)
    • (1998) IEEE Transactions on Fuzzy Systems , vol.6 , Issue.3 , pp. 373-388
    • Russo, M.1
  • 15
    • 0001847930 scopus 로고    scopus 로고
    • A GA-based fuzzy adaptive learning control network
    • I.F. Chung, C.J. Lin, and C.T. Lin A GA-based fuzzy adaptive learning control network Fuzzy Sets Syst. 112 1 2000 65 84
    • (2000) Fuzzy Sets Syst. , vol.112 , Issue.1 , pp. 65-84
    • Chung, I.F.1    Lin, C.J.2    Lin, C.T.3
  • 16
    • 0036531527 scopus 로고    scopus 로고
    • Evolution-based design of neural fuzzy networks using self-adapting genetic parameters
    • DOI 10.1109/91.995122, PII S1063670602029648
    • G. Alpaydin, G. Dandar, and S. Balkir Evolution-based design of neural fuzzy networks using self-adapting genetic parameters IEEE Trans. Fuzzy Syst. 10 2 2002 211 221 (Pubitemid 34554865)
    • (2002) IEEE Transactions on Fuzzy Systems , vol.10 , Issue.2 , pp. 211-221
    • Alpaydin, G.1    Dundar, G.2    Balkir, S.3
  • 17
    • 0142000477 scopus 로고    scopus 로고
    • Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
    • R. Storn, and K.V. Price Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces J. Global Opt. 11 December (4) 1997 341 359 (Pubitemid 127502202)
    • (1997) Journal of Global Optimization , vol.11 , Issue.4 , pp. 341-359
    • Storn, R.1    Price, K.2
  • 18
    • 0033115654 scopus 로고    scopus 로고
    • System design by constraint adaptation and differential evolution
    • APRIL 1
    • R. Storn System design by constraint adaptation and differential evolution IEEE Trans. Evol. Comput. 3 April (1) 1999 22 34
    • (1999) IEEE Trans. Evol. Comput. , vol.3 , pp. 22-34
    • Storn, R.1
  • 20
    • 78149253770 scopus 로고    scopus 로고
    • Differential evolution for high-dimensional function optimization
    • SEPTEMBER
    • Z. Yang, K. Tang, and X. Yao Differential evolution for high-dimensional function optimization IEEE Congress on Evolutionary Computation September 2007 3523 3530
    • (2007) IEEE Congress on Evolutionary Computation , pp. 3523-3530
    • Yang, Z.1    Tang, K.2    Yao, X.3
  • 21
    • 43849112481 scopus 로고    scopus 로고
    • Application of differential evolution algorithm for transient stability constrained optimal power flow
    • MAY 2
    • H.R. Cai, C.Y. Chung, and K.P. Wong Application of differential evolution algorithm for transient stability constrained optimal power flow IEEE Trans. Power Syst. 23 May (2) 2008 514 522
    • (2008) IEEE Trans. Power Syst. , vol.23 , pp. 514-522
    • Cai, H.R.1    Chung, C.Y.2    Wong, K.P.3
  • 24
    • 0032737896 scopus 로고    scopus 로고
    • Minimal representation multisensor fusion using differential evolution
    • JANUARY 1
    • R. Joshi, and A.C. Sanderson Minimal representation multisensor fusion using differential evolution IEEE Trans. Syst. Man Cybern. A 29 January (1) 1999 63 76
    • (1999) IEEE Trans. Syst. Man Cybern. A , vol.29 , pp. 63-76
    • Joshi, R.1    Sanderson, A.C.2
  • 26
    • 0033116436 scopus 로고    scopus 로고
    • Identification of nonlinear dynamic systems using functional link artificial neural networks
    • APRIL 2
    • J.C. Patra, R.N. Pal, B.N. Chatterji, and G. Panda Identification of nonlinear dynamic systems using functional link artificial neural networks IEEE Trans. Syst. Man Cybern. 29 April (2) 1999 254 262
    • (1999) IEEE Trans. Syst. Man Cybern. , vol.29 , pp. 254-262
    • Patra, J.C.1    Pal, R.N.2    Chatterji, B.N.3    Panda, G.4
  • 27
    • 0002318273 scopus 로고    scopus 로고
    • Efficient reinforcement learning through symbiotic evolution
    • D.E. Moriarty, and R. Miikkulainen Efficient reinforcement learning through symbiotic evolution Mach. Learn. 22 1996 11 32 (Pubitemid 126724361)
    • (1996) Machine Learning , vol.22 , Issue.1-3 , pp. 11-32
    • Moriarty, D.E.1    Miikkulainen, R.2
  • 29
    • 0026839028 scopus 로고
    • Nonlinear control via approximate input-output lineariztion: The ball and beam example
    • MARCH
    • J. Hauser, S. Sastry, and P. Kokotovic Nonlinear control via approximate input-output lineariztion: The ball and beam example IEEE Trans. Autom. Control. 37 March 1992 392 398
    • (1992) IEEE Trans. Autom. Control. , vol.37 , pp. 392-398
    • Hauser, J.1    Sastry, S.2    Kokotovic, P.3
  • 30
    • 0025418210 scopus 로고
    • The truck backer-upper: An example of self-learning in neural network
    • D. Nguyen, and B. Widrow The truck backer-upper: an example of self-learning in neural network IEEE Conf. Syst. Mag. 10 3 1990 18 23
    • (1990) IEEE Conf. Syst. Mag. , vol.10 , Issue.3 , pp. 18-23
    • Nguyen, D.1    Widrow, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.