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Volumn 16, Issue 6, 2008, Pages 1476-1490

Efficient self-evolving evolutionary learning for neurofuzzy inference systems

Author keywords

Cooperative particle swarm optimization CPSO); Cultural algorithm (CA); Elite based structure strategy ESS); Neurofuzzy inference system (NFIS); Symbiotic evolution

Indexed keywords

EDUCATION; FUZZY LOGIC; FUZZY RULES; FUZZY SETS; INFERENCE ENGINES; INFORMATION DISSEMINATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION; PARTICLE SWARM OPTIMIZATION (PSO); SOLUTE TRANSPORT; STRUCTURAL OPTIMIZATION;

EID: 58149517300     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2008.2005935     Document Type: Article
Times cited : (36)

References (52)
  • 1
    • 0027601884 scopus 로고
    • ANFIS: Adaptive-network-based fuzzy inference system
    • May/Jun
    • J.-S. R. Jang, "ANFIS: Adaptive-network-based fuzzy inference system," IEEE Trans. Syst., Man, Cybern., vol. 23, no. 3, pp. 665-685, May/Jun. 1993.
    • (1993) IEEE Trans. Syst., Man, Cybern , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.-S.R.1
  • 4
    • 0031268065 scopus 로고    scopus 로고
    • An ART-based fuzzy adaptive learning control network
    • Nov
    • C. J. Lin and C. T. Lin, "An ART-based fuzzy adaptive learning control network," IEEE Trans. Fuzzy Syst., vol. 5, no. 4, pp. 477-496, Nov. 1997.
    • (1997) IEEE Trans. Fuzzy Syst , vol.5 , Issue.4 , pp. 477-496
    • Lin, C.J.1    Lin, C.T.2
  • 5
    • 0031999146 scopus 로고    scopus 로고
    • An online self-constructing neural fuzzy inference network and its applications
    • Feb
    • C. F. Juang and C. T. Lin, "An online self-constructing neural fuzzy inference network and its applications," IEEE Trans. Fuzzy Syst., vol. 6, no. 1, pp. 12-31, Feb. 1998.
    • (1998) IEEE Trans. Fuzzy Syst , vol.6 , Issue.1 , pp. 12-31
    • Juang, C.F.1    Lin, C.T.2
  • 6
    • 0036530967 scopus 로고    scopus 로고
    • DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction
    • Apr
    • N. K. Kasabov and Q. Song, "DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction," IEEE Trans. Fuzzy Syst., vol. 10, no. 2, pp. 144-154, Apr. 2002.
    • (2002) IEEE Trans. Fuzzy Syst , vol.10 , Issue.2 , pp. 144-154
    • Kasabov, N.K.1    Song, Q.2
  • 7
    • 4844222566 scopus 로고    scopus 로고
    • Prediction and identification using wavelet-based recurrent fuzzy neural networks
    • Oct
    • C. J. Lin and C. C. Chin, "Prediction and identification using wavelet-based recurrent fuzzy neural networks," IEEE Trans. Syst., Man, Cybern., vol. 34, no. 5, pp. 2144-2154, Oct. 2004.
    • (2004) IEEE Trans. Syst., Man, Cybern , vol.34 , Issue.5 , pp. 2144-2154
    • Lin, C.J.1    Chin, C.C.2
  • 9
    • 0346781553 scopus 로고    scopus 로고
    • Ten years of genetic fuzzy systems: Current framework and newtrends
    • O. Cordon, F. Gomide, F. Herrera, F. Hoffmann, and L. Magdalena, "Ten years of genetic fuzzy systems: Current framework and newtrends," Fuzzy Sets Syst., vol. 141, no. 1, pp. 5-31, 2004.
    • (2004) Fuzzy Sets Syst , vol.141 , Issue.1 , pp. 5-31
    • Cordon, O.1    Gomide, F.2    Herrera, F.3    Hoffmann, F.4    Magdalena, L.5
  • 10
    • 33748894279 scopus 로고    scopus 로고
    • Genetic fuzzy systems: Status, critical considerations and future directions
    • F. Herrera, "Genetic fuzzy systems: Status, critical considerations and future directions," Int. J. Comput. Intell. Res., vol. 1, no. 1, pp. 59-67, 2005.
    • (2005) Int. J. Comput. Intell. Res , vol.1 , Issue.1 , pp. 59-67
    • Herrera, F.1
  • 11
    • 0031275420 scopus 로고    scopus 로고
    • Evolutionary design of a fuzzy knowledge base for a mobile robot
    • Nov
    • S. H. Stewart, S. Taylor, J. M. Baker, F. Hoffmann, and G. Pfister, "Evolutionary design of a fuzzy knowledge base for a mobile robot," Int. J. Approx. Reason., vol. 17, no. 4, pp. 447-469, Nov. 1997.
    • (1997) Int. J. Approx. Reason , vol.17 , Issue.4 , pp. 447-469
    • Stewart, S.H.1    Taylor, S.2    Baker, J.M.3    Hoffmann, F.4    Pfister, G.5
  • 13
    • 0032597810 scopus 로고    scopus 로고
    • Performance evaluation of fuzzy classifier systems for multi-dimensional pattern classification problems
    • Oct
    • H. Ishibuchi, T. Nakashima, and T. Murata, "Performance evaluation of fuzzy classifier systems for multi-dimensional pattern classification problems," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 29, no. 5, pp. 601-618, Oct. 1999.
    • (1999) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.29 , Issue.5 , pp. 601-618
    • Ishibuchi, H.1    Nakashima, T.2    Murata, T.3
  • 14
    • 0033317446 scopus 로고    scopus 로고
    • MOGUL: A methodology to obtain genetic fuzzy rule-based systems under the iterative rule learning approach
    • 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., vol. 14, no. 11, pp. 1123-1153, 1999.
    • (1999) Int. J. Intell. Syst , vol.14 , Issue.11 , pp. 1123-1153
    • Cordon, O.1    del Jesus, M.J.2    Herrera, F.3    Lozano, M.4
  • 15
    • 0033116171 scopus 로고    scopus 로고
    • SLAVE: A genetic learning system based on an iterative approach
    • Apr
    • A. Gonzalez and R. Perez, "SLAVE: A genetic learning system based on an iterative approach," IEEE Trans. Fuzzy Syst., vol. 7, no. 2, pp. 176-191, Apr. 1999.
    • (1999) IEEE Trans. Fuzzy Syst , vol.7 , Issue.2 , pp. 176-191
    • Gonzalez, A.1    Perez, R.2
  • 16
    • 0035897955 scopus 로고    scopus 로고
    • Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm
    • L. Castillo, A. Gonzalez, and R. Perez, "Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm," Fuzzy Sets Syst., vol. 120, no. 2, pp. 309-321, 2001.
    • (2001) Fuzzy Sets Syst , vol.120 , Issue.2 , pp. 309-321
    • Castillo, L.1    Gonzalez, A.2    Perez, R.3
  • 17
    • 0029359001 scopus 로고
    • Selecting fuzzy if-then rules for classification problems using genetic algorithms
    • Aug
    • H. Ishibuchi, K. Nozaki, N. Yamamoto, and H. Tanaka, "Selecting fuzzy if-then rules for classification problems using genetic algorithms," IEEE Trans. Fuzzy Syst., vol. 3, no. 3, pp. 260-270, Aug. 1995.
    • (1995) IEEE Trans. Fuzzy Syst , vol.3 , Issue.3 , pp. 260-270
    • Ishibuchi, H.1    Nozaki, K.2    Yamamoto, N.3    Tanaka, H.4
  • 18
    • 0000919523 scopus 로고    scopus 로고
    • Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems
    • H. Ishibuchi, T. Murata, and I. B. Turksen, "Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems," Fuzzy Sets Syst., vol. 89, no. 2, pp. 135-150, 1997.
    • (1997) Fuzzy Sets Syst , vol.89 , Issue.2 , pp. 135-150
    • Ishibuchi, H.1    Murata, T.2    Turksen, I.B.3
  • 19
    • 0035426682 scopus 로고    scopus 로고
    • Three-objective genetics-based machine learning for linguistic rule extraction
    • H. Ishibuchi, T. Nakashima, and T. Murata, "Three-objective genetics-based machine learning for linguistic rule extraction," Inf. Sci., vol. 136, no. 1-4, pp. 109-133, 2001.
    • (2001) Inf. Sci , vol.136 , Issue.1-4 , pp. 109-133
    • Ishibuchi, H.1    Nakashima, T.2    Murata, T.3
  • 20
    • 33751186914 scopus 로고    scopus 로고
    • Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning
    • H. Ishibuchi andY. Nojima, "Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning," Int. J. Approx. Reason., vol. 44, no. 1, pp. 4-31, 2007.
    • (2007) Int. J. Approx. Reason , vol.44 , Issue.1 , pp. 4-31
    • Ishibuchi andY, H.1    Nojima2
  • 21
    • 0029184523 scopus 로고
    • Fuzzy multi-layer perceptron, inferencing and rule generation
    • Jan
    • S. Mitra and S. K. Pal, "Fuzzy multi-layer perceptron, inferencing and rule generation," IEEE Trans. Neural Netw., vol. 6, no. 1, pp. 51-63, Jan. 1995.
    • (1995) IEEE Trans. Neural Netw , vol.6 , Issue.1 , pp. 51-63
    • Mitra, S.1    Pal, S.K.2
  • 22
    • 0030241728 scopus 로고    scopus 로고
    • Fuzzy self-organization, inferencing, and rule generation
    • Sep
    • S. Mitra and S. K. Pal, "Fuzzy self-organization, inferencing, and rule generation," IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 26, no. 5, pp. 608-620, Sep. 1996.
    • (1996) IEEE Trans. Syst., Man, Cybern. A, Syst., Humans , vol.26 , Issue.5 , pp. 608-620
    • Mitra, S.1    Pal, S.K.2
  • 23
    • 0034187785 scopus 로고    scopus 로고
    • Neurofuzzy rule generation: Survey in soft computing framework
    • May
    • S. Mitra and Y. Hayashi, "Neurofuzzy rule generation: Survey in soft computing framework," IEEE Trans. Neural Netw., vol. 11, no. 3, pp. 748-768, May 2000.
    • (2000) IEEE Trans. Neural Netw , vol.11 , Issue.3 , pp. 748-768
    • Mitra, S.1    Hayashi, Y.2
  • 24
    • 0036880603 scopus 로고    scopus 로고
    • Fuzzy decision tree, linguistic rules and fuzzy knowledge-based network: Generation and evaluation
    • Nov
    • S. Mitra, K. M. Konwar, and S. K. Pal, "Fuzzy decision tree, linguistic rules and fuzzy knowledge-based network: Generation and evaluation," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 32, no. 4, pp. 328-339, Nov. 2002.
    • (2002) IEEE Trans. Syst., Man, Cybern. C, Appl. Rev , vol.32 , Issue.4 , pp. 328-339
    • Mitra, S.1    Konwar, K.M.2    Pal, S.K.3
  • 25
    • 0037252858 scopus 로고    scopus 로고
    • Rough-fuzzy MLP: Modular evolution, rule generation, and evaluation
    • Jan./Feb
    • S. K. Pal, S. Mitra, and P. Mitra, "Rough-fuzzy MLP: Modular evolution, rule generation, and evaluation," IEEE Trans. Knowl. Data Eng., vol. 15, no. 1, pp. 14-25, Jan./Feb. 2003.
    • (2003) IEEE Trans. Knowl. Data Eng , vol.15 , Issue.1 , pp. 14-25
    • Pal, S.K.1    Mitra, S.2    Mitra, P.3
  • 26
    • 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., vol. 22, pp. 11-32, 1996.
    • (1996) Mach. Learn , vol.22 , pp. 11-32
    • Moriarty, D.E.1    Miikkulainen, R.2
  • 27
    • 0033705962 scopus 로고    scopus 로고
    • Genetic reinforcement learning through symbiotic evolution for fuzzy controller design
    • Apr
    • C. F. Juang, J. Y. Lin, and C. T. Lin, "Genetic reinforcement learning through symbiotic evolution for fuzzy controller design," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 30, no. 2, pp. 290-302, Apr. 2000.
    • (2000) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.30 , Issue.2 , pp. 290-302
    • Juang, C.F.1    Lin, J.Y.2    Lin, C.T.3
  • 28
    • 33644984844 scopus 로고    scopus 로고
    • A self-adaptive neural fuzzy network with group-based symbiotic evolution and its prediction applications
    • Apr
    • C. J. Lin and Y. J. Xu, "A self-adaptive neural fuzzy network with group-based symbiotic evolution and its prediction applications," Fuzzy Sets Syst., vol. 157, no. 8, pp. 1036-1056, Apr. 2006.
    • (2006) Fuzzy Sets Syst , vol.157 , Issue.8 , pp. 1036-1056
    • Lin, C.J.1    Xu, Y.J.2
  • 30
    • 33644678388 scopus 로고    scopus 로고
    • A hybrid evolutionary learning algorithm for TSK-type fuzzy model design
    • Mar
    • C. J. Lin and Y. J. Xu, "A hybrid evolutionary learning algorithm for TSK-type fuzzy model design," Math. Comput. Model., vol. 43, no. 5/6, pp. 563-581, Mar. 2006.
    • (2006) Math. Comput. Model , vol.43 , Issue.5-6 , pp. 563-581
    • Lin, C.J.1    Xu, Y.J.2
  • 31
    • 0029535737 scopus 로고
    • Particle swarm optimization
    • Perth, W.A, Australia, Nov./Dec
    • J. Kennedy and R. Eberhart, "Particle swarm optimization," in Proc. IEEE Int. Conf. Neural Netw., Perth, W.A., Australia, vol. 4, Nov./Dec.1995, pp. 1942-1948.
    • (1995) Proc. IEEE Int. Conf. Neural Netw , vol.4 , pp. 1942-1948
    • Kennedy, J.1    Eberhart, R.2
  • 32
    • 0029517385 scopus 로고
    • A new optimizer using particle swarm theory
    • Nagoya, Japan, Oct. 4-6
    • R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proc. 6th Int. Symp. Micro Mach. Hum. Sci., Nagoya, Japan, Oct. 4-6, 1995, pp. 39-43.
    • (1995) Proc. 6th Int. Symp. Micro Mach. Hum. Sci , pp. 39-43
    • Eberhart, R.1    Kennedy, J.2
  • 33
    • 2942539776 scopus 로고    scopus 로고
    • A particle swarm optimization approach for optimum design of PID controller in AVR system
    • Jun
    • Z. L. Gaing, "A particle swarm optimization approach for optimum design of PID controller in AVR system," IEEE Trans. Energy Convers., vol. 19, no. 2, pp. 384-391, Jun. 2004.
    • (2004) IEEE Trans. Energy Convers , vol.19 , Issue.2 , pp. 384-391
    • Gaing, Z.L.1
  • 34
    • 0034430526 scopus 로고    scopus 로고
    • A particle swarm optimization for reactive power and voltage control considering voltage security assessment
    • Nov
    • H. Yoshida, K. Kawata, Y. Fukuyama, S. Takayama, and Y. Nakanishi, "A particle swarm optimization for reactive power and voltage control considering voltage security assessment," IEEE Trans. Power Syst. vol. 15, no. 4, pp. 1232-1239, Nov. 2000.
    • (2000) IEEE Trans. Power Syst , vol.15 , Issue.4 , pp. 1232-1239
    • Yoshida, H.1    Kawata, K.2    Fukuyama, Y.3    Takayama, S.4    Nakanishi, Y.5
  • 35
    • 0036749163 scopus 로고    scopus 로고
    • Optimal design of power-system stabilizers using particle swarm optimization
    • Sep
    • M. A. Abido, "Optimal design of power-system stabilizers using particle swarm optimization," IEEE Trans. Energy Convers., vol. 17, no. 3, pp. 406-413, Sep. 2002.
    • (2002) IEEE Trans. Energy Convers , vol.17 , Issue.3 , pp. 406-413
    • Abido, M.A.1
  • 36
    • 1842535329 scopus 로고    scopus 로고
    • A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
    • Apr
    • C. F. Juang, "A hybrid of genetic algorithm and particle swarm optimization for recurrent network design," IEEE Trans. Syst., Man Cybern., vol. 34, no. 2, pp. 997-1006, Apr. 2004.
    • (2004) IEEE Trans. Syst., Man Cybern , vol.34 , Issue.2 , pp. 997-1006
    • Juang, C.F.1
  • 38
    • 3142697802 scopus 로고    scopus 로고
    • A cooperative approach to particle swarm optimization
    • Jun
    • F. Van Den Bergh and A. P. Engelbrecht, "A cooperative approach to particle swarm optimization," IEEE Trans. Evol. Comput., vol. 8, no. 3, pp. 225-239, Jun. 2004.
    • (2004) IEEE Trans. Evol. Comput , vol.8 , Issue.3 , pp. 225-239
    • Van Den Bergh, F.1    Engelbrecht, A.P.2
  • 39
    • 34548837472 scopus 로고    scopus 로고
    • A functional-link-based fuzzy neural network for temperature control
    • Honolulu, HI, Apr. 1-5, pp
    • C. H. Chen, C. T. Lin, and C. J. Lin, "A functional-link-based fuzzy neural network for temperature control," in Proc. 2007 IEEE Symp. Found. Comput. Intell., Honolulu, HI, Apr. 1-5, pp. 53-58.
    • Proc. 2007 IEEE Symp. Found. Comput. Intell , pp. 53-58
    • Chen, C.H.1    Lin, C.T.2    Lin, C.J.3
  • 40
    • 0033116436 scopus 로고    scopus 로고
    • Identification of nonlinear dynamic systems using functional link artificial neural networks
    • Apr
    • 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., vol. 29, no. 2, pp. 254-262, Apr. 1999.
    • (1999) IEEE Trans. Syst., Man, Cybern , vol.29 , Issue.2 , pp. 254-262
    • Patra, J.C.1    Pal, R.N.2    Chatterji, B.N.3    Panda, G.4
  • 41
    • 0002220448 scopus 로고
    • An introduction to cultural algorithms
    • A. V. Sebald and L. J. Fogel, Eds. River Edge, NJ: World Scientific
    • R. G. Reynolds, "An introduction to cultural algorithms," in Proc. 3rd Annu. Conf. Evol. Program., A. V. Sebald and L. J. Fogel, Eds. River Edge, NJ: World Scientific, 1994, pp. 131-139.
    • (1994) Proc. 3rd Annu. Conf. Evol. Program , pp. 131-139
    • Reynolds, R.G.1
  • 42
    • 84901434141 scopus 로고    scopus 로고
    • Using knowledge-based evolutionary computation to solve nonlinear constraint optimization problems: A cultural algorithm approach
    • Washington, DC
    • X. Jin and R. G. Reynolds, "Using knowledge-based evolutionary computation to solve nonlinear constraint optimization problems: A cultural algorithm approach," in Proc. IEEE Congr. Evol. Comput., Washington, DC, 1999, vol. 3, pp. 1672-1678.
    • (1999) Proc. IEEE Congr. Evol. Comput , vol.3 , pp. 1672-1678
    • Jin, X.1    Reynolds, R.G.2
  • 43
    • 23044535050 scopus 로고    scopus 로고
    • An empirical comparison of particle swarm and predator prey optimization
    • A. Silva, A. Neves, and E. Costa, "An empirical comparison of particle swarm and predator prey optimization," Lecture Notes Comput. Sci. vol. 2464, pp. 103-110, 2002.
    • (2002) Lecture Notes Comput. Sci , vol.2464 , pp. 103-110
    • Silva, A.1    Neves, A.2    Costa, E.3
  • 44
    • 52949135344 scopus 로고    scopus 로고
    • A modified particle swarm optimizer for the coordination of directional overcurrent relays
    • Jul
    • M. Mansour, S. F. Mekhamer, and N. E.-S. El-Kharbawe, "A modified particle swarm optimizer for the coordination of directional overcurrent relays," IEEE Trans. Power Del., vol. 22, no. 3, pp. 1400-1410, Jul. 2007.
    • (2007) IEEE Trans. Power Del , vol.22 , Issue.3 , pp. 1400-1410
    • Mansour, M.1    Mekhamer, S.F.2    El-Kharbawe, N.E.-S.3
  • 45
    • 4243745059 scopus 로고    scopus 로고
    • Knowledge-based solution to dynamic optimization problems using cultural algorithms,
    • Ph.D. dissertation, Wayne State Univ, Detroit, MI
    • S. M. Saleem, "Knowledge-based solution to dynamic optimization problems using cultural algorithms," Ph.D. dissertation, Wayne State Univ., Detroit, MI, 2001.
    • (2001)
    • Saleem, S.M.1
  • 46
    • 0003093755 scopus 로고    scopus 로고
    • Predicting the Mackey-Glass time series with cascade-correlation learning
    • R. S. Cowder, "Predicting the Mackey-Glass time series with cascade-correlation learning," in Proc. 1990 Connectionist Models Summer School, pp. 117-123.
    • Proc. 1990 Connectionist Models Summer School , pp. 117-123
    • Cowder, R.S.1
  • 47
    • 0042525889 scopus 로고    scopus 로고
    • A novel genetic-algorithm-based neural network for short-term load forecasting
    • Aug
    • S. H. Ling, F. H. F. Leung, H. K. Lam,Y. S. Lee, and P.K. S. Tam, "A novel genetic-algorithm-based neural network for short-term load forecasting," IEEE Trans. Ind. Electron., vol. 50, no. 4, pp. 793-799, Aug. 2003.
    • (2003) IEEE Trans. Ind. Electron , vol.50 , Issue.4 , pp. 793-799
    • Ling, S.H.1    Leung, F.H.F.2    Lam, H.K.3    Lee, Y.S.4    Tam, P.K.S.5
  • 48
    • 0025418210 scopus 로고
    • The truck backer-upper: An example of self-learning in neural network
    • Apr
    • D. Nguyen and B. Widrow, "The truck backer-upper: An example of self-learning in neural network," IEEE Control Syst. Mag., vol. 10, no. 3, pp. 18-23, Apr. 1990.
    • (1990) IEEE Control Syst. Mag , vol.10 , Issue.3 , pp. 18-23
    • Nguyen, D.1    Widrow, B.2
  • 49
    • 1642311384 scopus 로고    scopus 로고
    • A GA-based neural fuzzy system for temperature control
    • Apr
    • C. J. Lin, "A GA-based neural fuzzy system for temperature control," Fuzzy Sets Syst., vol. 143, no. 2, pp. 311-333, Apr. 2004.
    • (2004) Fuzzy Sets Syst , vol.143 , Issue.2 , pp. 311-333
    • Lin, C.J.1
  • 50
    • 0026998481 scopus 로고
    • A learning method of fuzzy inference rules by descent method
    • San Diego, CA, Mar
    • H. Nomura, I. Hayashi, and N. Wakami, "A learning method of fuzzy inference rules by descent method," in Proc. IEEE Conf. Fuzzy Syst. San Diego, CA, Mar. 1992, pp. 203-210.
    • (1992) Proc. IEEE Conf. Fuzzy Syst , pp. 203-210
    • Nomura, H.1    Hayashi, I.2    Wakami, N.3
  • 51
    • 0036530772 scopus 로고    scopus 로고
    • A fast and elitist multiobjective genetic algorithm: NSGA-II
    • Apr
    • K. Deb, A. Pratap, S. Agrawal, and T. Meyarian, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE Trans. Evol. Comput., vol. 6, no. 2, pp. 182-197, Apr. 2002.
    • (2002) IEEE Trans. Evol. Comput , vol.6 , Issue.2 , pp. 182-197
    • Deb, K.1    Pratap, A.2    Agrawal, S.3    Meyarian, T.4
  • 52
    • 33845912160 scopus 로고    scopus 로고
    • Identification of strategy parameters for particle swarm optimizer through Taguchi method
    • A. Khosla, S. Kumar, and K. K. Aggarwal, "Identification of strategy parameters for particle swarm optimizer through Taguchi method," J. Zhejiang Univ. Sci., vol. 7, no. 12, pp. 1989-1994, 2006.
    • (2006) J. Zhejiang Univ. Sci , vol.7 , Issue.12 , pp. 1989-1994
    • Khosla, A.1    Kumar, S.2    Aggarwal, K.K.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.