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Volumn 214, Issue 3, 2011, Pages 644-655

Simulation metamodeling with dynamic Bayesian networks

Author keywords

Discrete event simulation; Dynamic Bayesian networks; Simulation; Simulation metamodeling

Indexed keywords

BAYESIAN NETWORKS; DISCRETE EVENT SIMULATION; PROBABILITY DISTRIBUTIONS; RANDOM VARIABLES;

EID: 84858061861     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2011.05.007     Document Type: Article
Times cited : (25)

References (41)
  • 1
    • 0004312378 scopus 로고    scopus 로고
    • fourth ed., McGraw-Hill Science/Engineering/Math, New York, NY
    • A. Law, Simulation Modeling and Analysis, fourth ed., McGraw-Hill Science/Engineering/Math, New York, NY, 2006.
    • (2006) Simulation Modeling and Analysis
    • Law, A.1
  • 5
    • 28044468130 scopus 로고
    • The sources and uses of sensitivity information
    • R.W. Blanning, The sources and uses of sensitivity information, Interfaces 4 (4) (1974) 32-38.
    • (1974) Interfaces , vol.4 , Issue.4 , pp. 32-38
    • Blanning, R.W.1
  • 8
    • 0036532658 scopus 로고    scopus 로고
    • Metamodeling: Radial basis functions, versus polynomials
    • DOI 10.1016/S0377-2217(01)00076-5, PII S0377221701000765
    • M. Hussain, R. Barton, S. Joshi, Metamodeling: Radial basis functions, versus polynomials, European Journal of Operational Research 138 (1) (2002) 142-154. (Pubitemid 34040607)
    • (2002) European Journal of Operational Research , vol.138 , Issue.1 , pp. 142-154
    • Hussain, M.F.1    Barton, R.R.2    Joshi, S.B.3
  • 9
    • 77951184800 scopus 로고    scopus 로고
    • Stochastic kriging for simulation metamodeling
    • B. Ankenman, B.L. Nelson, J. Staum, Stochastic kriging for simulation metamodeling, Operations Research 58 (2) (2010) 371-382.
    • (2010) Operations Research , vol.58 , Issue.2 , pp. 371-382
    • Ankenman, B.1    Nelson, B.L.2    Staum, J.3
  • 10
    • 0023401029 scopus 로고
    • Experimental procedure for simulation response surface model identification
    • DOI 10.1145/27651.27656
    • L.W. Schruben, V.J. Cogliano, An experimental procedure for simulation response surface model identification, Communication of the Association for Computing Machinery 30 (8) (1987) 716-730. (Pubitemid 17657416)
    • (1987) Communications of the ACM , vol.30 , Issue.8 , pp. 716-730
    • Schruben Lee, W.1    Cogliano V.James2
  • 11
  • 15
    • 61349137704 scopus 로고    scopus 로고
    • Improving maintenance decision making in the Finnish air force through simulation
    • V.A. Mattila, K. Virtanen, T. Raivio, Improving maintenance decision making in the Finnish air force through simulation, Interfaces 38 (3) (2008) 187-201.
    • (2008) Interfaces , vol.38 , Issue.3 , pp. 187-201
    • Mattila, V.A.1    Virtanen, K.2    Raivio, T.3
  • 16
    • 84990553353 scopus 로고
    • A model for reasoning about persistence and causation
    • T. Dean, K. Kanazawa, A model for reasoning about persistence and causation, Computational Intelligence 5 (3) (1990) 142-150.
    • (1990) Computational Intelligence , vol.5 , Issue.3 , pp. 142-150
    • Dean, T.1    Kanazawa, K.2
  • 17
    • 49749105218 scopus 로고    scopus 로고
    • Analyzing air combat simulation results with dynamic Bayesian networks
    • Washington, DC
    • J. Poropudas, K. Virtanen, Analyzing air combat simulation results with dynamic Bayesian networks, in: Proceedings of the 2007 Winter Simulation Conference, Washington, DC, 2007, pp. 1370-1377.
    • (2007) Proceedings of the 2007 Winter Simulation Conference , pp. 1370-1377
    • Poropudas, J.1    Virtanen, K.2
  • 19
    • 0003448310 scopus 로고    scopus 로고
    • (Information Science and Statistics) Springer-Verlag, New York, NY
    • F.V. Jensen, Bayesian Networks and Decision Graphs (Information Science and Statistics), Springer-Verlag, New York, NY, 2001.
    • (2001) Bayesian Networks and Decision Graphs
    • Jensen, F.V.1
  • 24
    • 0002370418 scopus 로고    scopus 로고
    • MIT Press, Cambridge, MA (Chapter A tutorial on learning with Bayesian networks)
    • D. Heckerman, Learning in Graphical Models, MIT Press, Cambridge, MA, 1999. pp. 301-354 (Chapter A tutorial on learning with Bayesian networks).
    • (1999) Learning in Graphical Models , pp. 301-354
    • Heckerman, D.1
  • 28
    • 4344578226 scopus 로고    scopus 로고
    • Bayesian networks for data mining
    • D. Heckerman, Bayesian networks for data mining, Data Mining and Knowledge Discovery 1 (1) (1997) 79-119. (Pubitemid 127721237)
    • (1997) Data Mining and Knowledge Discovery , vol.1 , Issue.1 , pp. 79-119
    • Heckerman, D.1
  • 29
    • 0030124955 scopus 로고    scopus 로고
    • A guide to the literature on learning probabilistic networks from data
    • W. Buntine, A guide to the literature on learning probabilistic networks from data, IEEE Transactions on Knowledge and Data Engineering 8 (2) (1996) 195-210. (Pubitemid 126776290)
    • (1996) IEEE Transactions on Knowledge and Data Engineering , vol.8 , Issue.2 , pp. 195-210
    • Buntine, W.1
  • 31
    • 85030579722 scopus 로고    scopus 로고
    • graphical network interface, (accessed 17.02.10)
    • Decision Systems Laboratory, GeNIe (graphical network interface). Available from: , 2010 (accessed 17.02.10).
    • (2010) Decision Systems Laboratory GeNIe
  • 33
    • 28044453106 scopus 로고    scopus 로고
    • Statistical fitting and validation of nonlinear simulation metamodels: A case study
    • M.I.R. dos Santos, A.M. Porta Nova, Statistical fitting and validation of nonlinear simulation metamodels: A case study, European Journal of Operational Research 171 (1) (2006) 53-63.
    • (2006) European Journal of Operational Research , vol.171 , Issue.1 , pp. 53-63
    • Dos Santos, M.I.R.1    Porta Nova, A.M.2
  • 34
    • 33750997027 scopus 로고    scopus 로고
    • Discovering metamodels' quality-of-fit for simulation via graphical techniques
    • DOI 10.1016/j.ejor.2006.01.026, PII S0377221706000701
    • H. Hamad, S. Al-Hamdan, Discovering metamodels' quality-of-fit for simulation via graphical techniques, European Journal of Operational Research 178 (2) (2007) 543-559. (Pubitemid 44750479)
    • (2007) European Journal of Operational Research , vol.178 , Issue.2 , pp. 543-559
    • Hamad, H.1    Al-Hamdan, S.2
  • 35
    • 0000460102 scopus 로고    scopus 로고
    • Interval Estimation for a Binomial Proportion
    • L.D. Brown, T.T. Cai, A. DasGupta, Interval estimation for a binomial proportion, Statistical Science 16 (2) (2001) 101-133. (Pubitemid 33636344)
    • (2001) Statistical Science , vol.16 , Issue.2 , pp. 101-133
    • Brown, L.D.1    Cai, T.T.2    DasGupta, A.3
  • 36
    • 0025401005 scopus 로고
    • The computational complexity of probabilistic inference using Bayesian belief networks (research note)
    • G.F. Cooper, The computational complexity of probabilistic inference using Bayesian belief networks (research note), Artificial Intelligence 42 (2-3) (1990) 393-405.
    • (1990) Artificial Intelligence , vol.42 , Issue.2-3 , pp. 393-405
    • Cooper, G.F.1
  • 39
    • 25844480252 scopus 로고    scopus 로고
    • Validation of regression metamodels in simulation: Bootstrap approach
    • DOI 10.1016/j.ejor.2004.06.018, PII S0377221704004576
    • J.P. Kleijnen, D. Deflandre, Validation of regression metamodels in simulation: Bootstrap approach, European Journal of Operational Research 170 (1) (2006) 120-131. (Pubitemid 41400624)
    • (2006) European Journal of Operational Research , vol.170 , Issue.1 , pp. 120-131
    • Kleijnen, J.P.C.1    Deflandre, D.2
  • 41
    • 0141503453 scopus 로고    scopus 로고
    • Multi-agent influence diagrams for representing and solving games
    • DOI 10.1016/S0899-8256(02)00544-4
    • D. Koller, B. Milch, Multi-agent influence diagrams for representing and solving games, Games and Economic Behavior 45 (1) (2003) 181-221. (Pubitemid 37194965)
    • (2003) Games and Economic Behavior , vol.45 , Issue.1 , pp. 181-221
    • Koller, D.1    Milch, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.