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Volumn , Issue , 2011, Pages 675-679

Deformation prediction of landslide based on genetic-simulated annealing algorithm and BP neural network

Author keywords

[No Author keywords available]

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; BP NEURAL NETWORKS; COMPLEX NONLINEAR RELATION; DEFORMATION PREDICTION; DYNAMIC PREDICTION; GENETIC SIMULATED ANNEALING ALGORITHMS; LANDSLIDE DEFORMATION; LANDSLIDE PREDICTION; LEARNING MODELS; LEARNING SPEED; SIMULATED ANNEALING ALGORITHMS; THREE GORGES RESERVOIR;

EID: 84863340442     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IWACI.2011.6160092     Document Type: Conference Paper
Times cited : (7)

References (11)
  • 2
    • 38149109867 scopus 로고    scopus 로고
    • Artificial Neural Networks and Cluster Analysis in Landslide Susceptibility Zonation
    • C. Melchiorre, M. Matteucci, A. Azzoni, and A. Zanchi, "Artificial Neural Networks and Cluster Analysis in Landslide Susceptibility Zonation," Geomorphology, vol.94, pp. 379-400, 2008.
    • (2008) Geomorphology , vol.94 , pp. 379-400
    • Melchiorre, C.1    Matteucci, M.2    Azzoni, A.3    Zanchi, A.4
  • 3
    • 77149157821 scopus 로고    scopus 로고
    • Regional Landslide Susceptibility Analysis Using Back-propagation Neural Network Model at Cameron Highland, Malaysia
    • B. Pradhan and S. Lee, "Regional Landslide Susceptibility Analysis Using Back-propagation Neural Network Model at Cameron Highland, Malaysia," Landslide, vol. 7, pp. 13-30, 2010.
    • (2010) Landslide , vol.7 , pp. 13-30
    • Pradhan, B.1    Lee, S.2
  • 4
    • 36849021068 scopus 로고    scopus 로고
    • Landslide Susceptibility Analysis and its Verification Using Likelihood Ratio, Logistic Regression, and Artificial Neural Network Models: Case Study of Youngin, Korea
    • S. Lee, J. H. Ryu, and I. S. Kim, "Landslide Susceptibility Analysis and its Verification Using Likelihood Ratio, Logistic Regression, and Artificial Neural Network Models: Case Study of Youngin, Korea,"Landslides, vol. 4, pp. 327-338, 2007.
    • (2007) Landslides , vol.4 , pp. 327-338
    • Lee, S.1    Ryu, J.H.2    Kim, I.S.3
  • 5
    • 76749088419 scopus 로고    scopus 로고
    • Landslide Susceptibility Assessment and Factor Effect Analysis: Backpropagation Artificial Neural Networks and their Comparison with Frequency Ratio and Bivariate Logistic Regression Modelling
    • B. Pradhan and S. Lee, "Landslide Susceptibility Assessment and Factor Effect Analysis: Backpropagation Artificial Neural Networks and their Comparison with Frequency Ratio and Bivariate Logistic Regression Modelling," Environmental Modelling & Software, vol. 25, pp. 747-2010.
    • Environmental Modelling & Software , vol.25 , pp. 747-2010
    • Pradhan, B.1    Lee, S.2
  • 6
    • 3042850464 scopus 로고    scopus 로고
    • Study on Displacement Predication of Landslide based on Grey System and Evolutionary Neural Network
    • W. Gao and X. Feng, "Study on Displacement Predication of Landslide based on Grey System and Evolutionary Neural Network", Rock and Soil Mechanics, vol. 25, no. 4, pp. 514-17, 2004.
    • (2004) Rock and Soil Mechanics , vol.25 , Issue.4 , pp. 514-517
    • Gao, W.1    Feng, X.2
  • 8
    • 0026953305 scopus 로고
    • Improving Generalization Using Double Back Propagation
    • H. Ducker and Y. L. Cuny, "Improving Generalization Using Double Back Propagation," IEEE Trans. on Neural Networks, vol. 3, no. 6, pp. 991-997, 1992.
    • (1992) IEEE Trans. on Neural Networks , vol.3 , Issue.6 , pp. 991-997
    • Ducker, H.1    Cuny, Y.L.2
  • 11
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • DOI 10.1016/0893-6080(89)90020-8
    • K. M. Hornik, M. Stinchcombe, and H. White, "Multilayer Feedforward Networks are Universal Approximators," Neural Networks, 2, pp. 359-366, 1989. (Pubitemid 20609008)
    • (1989) Neural Networks , vol.2 , Issue.5 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.