메뉴 건너뛰기




Volumn 35, Issue 3, 2009, Pages 281-288

Bayesian network learning algorithm based on independence test and ant colony optimization

Author keywords

Ant colony optimization (ACO); Bayesian network structure learning; Conditional independence test; Uncertainty modeling

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; DISTRIBUTED PARAMETER NETWORKS; EDUCATION; HEURISTIC ALGORITHMS; HEURISTIC METHODS; INFERENCE ENGINES; INTELLIGENT NETWORKS; KNOWLEDGE BASED SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; OPTIMIZATION; SPEECH ANALYSIS; SPEECH RECOGNITION; STATISTICAL TESTS; TESTING;

EID: 63749120518     PISSN: 02544156     EISSN: None     Source Type: Journal    
DOI: 10.3724/SP.J.1004.2009.00281     Document Type: Article
Times cited : (47)

References (22)
  • 3
    • 0036567524 scopus 로고    scopus 로고
    • Learning Bayesian networks from data: An information theory based approach
    • Cheng J, Greiner R, Kelly J, Bell D, Liu W. Learning Bayesian networks from data: an information theory based approach. Artificial Intelligence, 2002, 137(1-2): 43-90.
    • (2002) Artificial Intelligence , vol.137 , Issue.1-2 , pp. 43-90
    • Cheng, J.1    Greiner, R.2    Kelly, J.3    Bell, D.4    Liu, W.5
  • 4
    • 0008580731 scopus 로고    scopus 로고
    • Learning Bayesian belief networks based on the minimum description length principle: Basic properties
    • Suzuki J. Learning Bayesian belief networks based on the minimum description length principle: basic properties. IEICE Transactions on Fundamentals, 1999, 82(10): 2237-2245.
    • (1999) IEICE Transactions on Fundamentals , vol.82 , Issue.10 , pp. 2237-2245
    • Suzuki, J.1
  • 8
    • 0033076357 scopus 로고    scopus 로고
    • Using evolutionary programming and minimum description length principle for data mining of Bayesian networks
    • Wong M L, Lam W, Leung K S. Using evolutionary programming and minimum description length principle for data mining of Bayesian networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(2): 174-178.
    • (1999) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.21 , Issue.2 , pp. 174-178
    • Wong, M.L.1    Lam, W.2    Leung, K.S.3
  • 9
    • 0036132536 scopus 로고    scopus 로고
    • Searching for the best elimination sequence in Bayesian networks by using ant colony optimization
    • Jose A G, Jose M P. Searching for the best elimination sequence in Bayesian networks by using ant colony optimization. Pattern Recognition Letters, 2002, 23(1-3): 261-277.
    • (2002) Pattern Recognition Letters , vol.23 , Issue.1-3 , pp. 261-277
    • Jose, A.G.1    Jose, M.P.2
  • 11
  • 12
    • 34248651851 scopus 로고    scopus 로고
    • A fast Bayesian network structure learning algorithm
    • in Chinese
    • Ji Jun-Zhong, Liu Chun-Nian, Yan Jing. A fast Bayesian network structure learning algorithm. Journal of Computer Research and Development, 2007, 44(3): 412-419 (in Chinese).
    • (2007) Journal of Computer Research and Development , vol.44 , Issue.3 , pp. 412-419
    • Ji, J.-Z.1    Liu, C.-N.2    Yan, J.3
  • 13
    • 4444383943 scopus 로고    scopus 로고
    • An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach
    • Wong M L, Leung K S. An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach. IEEE Transactions on Evolutionary Computation, 2004, 8(4): 378-404.
    • (2004) IEEE Transactions on Evolutionary Computation , vol.8 , Issue.4 , pp. 378-404
    • Wong, M.L.1    Leung, K.S.2
  • 14
    • 33645281928 scopus 로고    scopus 로고
    • A simulated annealing-based method for learning Bayesian networks from statistical data: Research articles
    • Mantin J, Jan N. A simulated annealing-based method for learning Bayesian networks from statistical data: research articles. International Journal of Intelligent Systems, 2006, 21(3): 335-348.
    • (2006) International Journal of Intelligent Systems , vol.21 , Issue.3 , pp. 335-348
    • Mantin, J.1    Jan, N.2
  • 15
    • 33746035971 scopus 로고    scopus 로고
    • The max-min hill-climbing Bayesian network structure learning algorithm
    • Tsamardinos I, Brown L E, Alieris C F. The max-min hill-climbing Bayesian network structure learning algorithm. Machine Learning, 2006, 65(1): 31-78.
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 31-78
    • Tsamardinos, I.1    Brown, L.E.2    Alieris, C.F.3
  • 16
    • 31844445716 scopus 로고    scopus 로고
    • Incremental hill-climbing search applied to Bayesian network structure learning
    • Pisa, Italy: IEEE
    • Alcobe J R. Incremental hill-climbing search applied to Bayesian network structure learning. In: Proceedings of the 15th European Conference on Machine Learning. Pisa, Italy: IEEE, 2004. 1-10.
    • (2004) Proceedings of the 15th European Conference on Machine Learning , pp. 1-10
    • Alcobe, J.R.1
  • 18
    • 0031122887 scopus 로고    scopus 로고
    • Ant colony system: A cooperative learning approach to the traveling salesman problem
    • Dorigo M, Gambardella L M. Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 53-66.
    • (1997) IEEE Transactions on Evolutionary Computation , vol.1 , Issue.1 , pp. 53-66
    • Dorigo, M.1    Gambardella, L.M.2
  • 19
    • 17644402086 scopus 로고    scopus 로고
    • Search bias in ant colony optimization: On the role of competition-balanced systems
    • Blum C, Dorigo M. Search bias in ant colony optimization: on the role of competition-balanced systems. IEEE Transactions on Evolutionary Computation, 2005, 9(2): 159-174.
    • (2005) IEEE Transactions on Evolutionary Computation , vol.9 , Issue.2 , pp. 159-174
    • Blum, C.1    Dorigo, M.2
  • 21
    • 0036670452 scopus 로고    scopus 로고
    • A short convergence proof for a class of ant colony optimization algorithms
    • Stutzle T, Dorigo M. A short convergence proof for a class of ant colony optimization algorithms. IEEE Transactions on Evolutionary Computation, 2002, 6(4): 358-365.
    • (2002) IEEE Transactions on Evolutionary Computation , vol.6 , Issue.4 , pp. 358-365
    • Stutzle, T.1    Dorigo, M.2
  • 22
    • 33846280533 scopus 로고    scopus 로고
    • Ant colony optimization: Artificial ants as a computational intelligence technique
    • Dorigo M, Birattari M, Stutzle T. Ant colony optimization: artificial ants as a computational intelligence technique. IEEE Computational Intelligence Magazine, 2006, 1(4): 28-39.
    • (2006) IEEE Computational Intelligence Magazine , vol.1 , Issue.4 , pp. 28-39
    • Dorigo, M.1    Birattari, M.2    Stutzle, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.