메뉴 건너뛰기




Volumn 4688 LNCS, Issue , 2007, Pages 287-296

Genetic particle swarm optimization based on estimation of distribution

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; MATHEMATICAL MODELS; PROBABILITY; PROBLEM SOLVING; STATISTICAL METHODS;

EID: 38049086157     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74769-7_32     Document Type: Conference Paper
Times cited : (9)

References (18)
  • 2
    • 0002345372 scopus 로고    scopus 로고
    • Cooperative Learning in Neural Network Using Particle Swarm Optimizers
    • Van den Bergh, F., Engelbrecht, A.P.: Cooperative Learning in Neural Network Using Particle Swarm Optimizers. South African Computer Journal 26, 84-90 (2000)
    • (2000) South African Computer Journal , vol.26 , pp. 84-90
    • Van den Bergh, F.1    Engelbrecht, A.P.2
  • 4
    • 0344291226 scopus 로고    scopus 로고
    • Recent approaches to global optimization problems through Particle Swarm Optimization
    • Parsopoulos, K.E., Vrahatis, M.N.: Recent approaches to global optimization problems through Particle Swarm Optimization. Natural Computing 1(2-3), 235-306 (2002)
    • (2002) Natural Computing , vol.1 , Issue.2-3 , pp. 235-306
    • Parsopoulos, K.E.1    Vrahatis, M.N.2
  • 6
    • 27144516371 scopus 로고    scopus 로고
    • Investigating Binary PSO Parameter Influence on the Knights Cover Problem
    • Franken, N., Engelbrecht, A.P.: Investigating Binary PSO Parameter Influence on the Knights Cover Problem. IEEE Congress on Evolutionary Computation 1, 282289 (2005)
    • (2005) IEEE Congress on Evolutionary Computation , vol.1 , pp. 282289
    • Franken, N.1    Engelbrecht, A.P.2
  • 9
    • 33746099660 scopus 로고    scopus 로고
    • Genetic Particle Swarm Optimization for Polygonal Approximation of Digital Curves
    • Yin, P.Y.: Genetic Particle Swarm Optimization for Polygonal Approximation of Digital Curves. Pattern Recognition and Image Analysis 16(2), 223-233 (2006)
    • (2006) Pattern Recognition and Image Analysis , vol.16 , Issue.2 , pp. 223-233
    • Yin, P.Y.1
  • 10
    • 38049031463 scopus 로고    scopus 로고
    • Mühlenbein, H., Paaβ, G.: From Recombination of Genes to the Estimation of Distributions. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN IV. LNCS, 1141, pp. 178-187. Springer, Heidelberg (1996)
    • Mühlenbein, H., Paaβ, G.: From Recombination of Genes to the Estimation of Distributions. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN IV. LNCS, vol. 1141, pp. 178-187. Springer, Heidelberg (1996)
  • 12
    • 4344707250 scopus 로고    scopus 로고
    • Learning Probability Distributions in Continuous Evolutionary Algorithms-A Comparative Review
    • Kern, S., Muller, S.D., Hansen, N., Buche, D., Ocenasek, J., Koumoutsakos, P.: Learning Probability Distributions in Continuous Evolutionary Algorithms-A Comparative Review. Natural Computing 3(1), 77-112 (2004)
    • (2004) Natural Computing , vol.3 , Issue.1 , pp. 77-112
    • Kern, S.1    Muller, S.D.2    Hansen, N.3    Buche, D.4    Ocenasek, J.5    Koumoutsakos, P.6
  • 13
    • 1642357278 scopus 로고    scopus 로고
    • Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
    • Springer, Heidelberg
    • Larrañaga, P., Lozano, J.: Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation. In: Genetic Algorithms and Evolutionary Computation, vol. 2, Springer, Heidelberg (2001)
    • (2001) Genetic Algorithms and Evolutionary Computation , vol.2
    • Larrañaga, P.1    Lozano, J.2
  • 14
    • 0031215849 scopus 로고    scopus 로고
    • The Equation for Response to Selection and Its Use for Prediction
    • Müehlenbein, H.: The Equation for Response to Selection and Its Use for Prediction. Evol. Comput. 5(3), 303-346 (1997)
    • (1997) Evol. Comput , vol.5 , Issue.3 , pp. 303-346
    • Müehlenbein, H.1
  • 15
    • 0003984832 scopus 로고
    • Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning. School of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA
    • Tech. Rep. CMU-CS-94-163
    • Baluja, S.: Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning. School of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, Tech. Rep. CMU-CS-94-163 (1994)
    • (1994)
    • Baluja, S.1
  • 17
    • 12244265523 scopus 로고    scopus 로고
    • Where Are the Hard Knapsack Problem?
    • Pisinger, D.: Where Are the Hard Knapsack Problem? Computer & Operations Research 32, 271-2284 (2006)
    • (2006) Computer & Operations Research , vol.32 , pp. 271-2284
    • Pisinger, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.