메뉴 건너뛰기




Volumn 10, Issue 1, 2009, Pages 101-108

Assessment of highway slope failure using neural networks

Author keywords

Eural network; Highway; Prediction; Slope failure

Indexed keywords

ARTIFICIAL INTELLIGENCE TECHNIQUES; ARTIFICIAL NEURAL NETWORKS; BACK-PROPAGATION NEURAL NETWORKS; CUMULATIVE PRECIPITATIONS; DAILY RAINFALLS; EURAL NETWORK; HIGHWAY; HIGHWAY SLOPES; NEURAL NETWORK MODELS; NUMERICAL RESULTS; PREDICTION; SLOPE FAILURE; SLOPE GRADIENTS; SOUTHERN TAIWAN;

EID: 62349133502     PISSN: 1673565X     EISSN: 18621775     Source Type: Journal    
DOI: 10.1631/jzus.A0820265     Document Type: Article
Times cited : (23)

References (29)
  • 1
    • 0035480452 scopus 로고    scopus 로고
    • Investigating the role of saliency analysis with neural network rainfall-runoff model
    • R.J. Abrahart L. See P.E. Kneal 2001 Investigating the role of saliency analysis with neural network rainfall-runoff model Computers & Geosciences 27 8 921 928
    • (2001) Computers & Geosciences , vol.27 , Issue.8 , pp. 921-928
    • Abrahart, R.J.1    See, L.2    Kneal, P.E.3
  • 2
    • 0018918084 scopus 로고
    • The rainfall intensity-duration control of shallow landslides and debris flow
    • N. Caine 1980 The rainfall intensity-duration control of shallow landslides and debris flow Geografiska Annaler Series A, Physical Geography 62 1/2 23 27
    • (1980) Geografiska Annaler Series A, Physical Geography , vol.62 , Issue.1-2 , pp. 23-27
    • Caine, N.1
  • 3
    • 0032688155 scopus 로고    scopus 로고
    • River flood forecasting with a neural network model
    • M. Campolo P. Andreussi A. Soldati 1999 River flood forecasting with a neural network model Water Resources Research 35 4 1191 1197
    • (1999) Water Resources Research , vol.35 , Issue.4 , pp. 1191-1197
    • Campolo, M.1    Andreussi, P.2    Soldati, A.3
  • 4
    • 0000487452 scopus 로고
    • Rainfall conditions for abundant debris avalanches in San Francisco Bay region, California
    • S.H. Cannon S.D. Ellen 1985 Rainfall conditions for abundant debris avalanches in San Francisco Bay region, California California Geology 38 12 267 272
    • (1985) California Geology , vol.38 , Issue.12 , pp. 267-272
    • Cannon, S.H.1    Ellen, S.D.2
  • 5
    • 0344286516 scopus 로고    scopus 로고
    • Real time wave forecasting using neural networks
    • M.C. Deo C.S. Naidu 1998 Real time wave forecasting using neural networks Ocean Engineering 26 3 191 303
    • (1998) Ocean Engineering , vol.26 , Issue.3 , pp. 191-303
    • Deo, M.C.1    Naidu, C.S.2
  • 7
    • 0002222232 scopus 로고    scopus 로고
    • Landslide risk management
    • Cruden, D., Fell, R. (Ed.) Balkema, Rotterdam
    • Fell, R., Hartford, D., 1997. Landslide Risk Management. In: Cruden, D., Fell, R. (Ed.), Landslide Risk Assessment, Balkema, Rotterdam, p.51-109.
    • (1997) Landslide Risk Assessment , pp. 51-109
    • Fell, R.1    Hartford, D.2
  • 8
    • 0027007868 scopus 로고
    • Rainfall forecasting in space and time using a neural network
    • M.N. French W.F. Krajewski R.R. Cuykendall 1992 Rainfall forecasting in space and time using a neural network Journal of Hydrology 137 1-4 1 31
    • (1992) Journal of Hydrology , vol.137 , Issue.1-4 , pp. 1-31
    • French, M.N.1    Krajewski, W.F.2    Cuykendall, R.R.3
  • 10
    • 0027812765 scopus 로고
    • Some new results on neural network approximation
    • K. Hornik 1993 Some new results on neural network approximation Neural Networks 6 9 1069 1072
    • (1993) Neural Networks , vol.6 , Issue.9 , pp. 1069-1072
    • Hornik, K.1
  • 11
    • 0024137490 scopus 로고
    • Increased rates of convergence through learning rate adaptation
    • R.A. Jacobs 1988 Increased rates of convergence through learning rate adaptation Neural Network 1 4 295 307
    • (1988) Neural Network , vol.1 , Issue.4 , pp. 295-307
    • Jacobs, R.A.1
  • 14
    • 0344062921 scopus 로고    scopus 로고
    • Back-propagation neural network for long-term tidal predictions
    • T.L. Lee 2004 Back-propagation neural network for long-term tidal predictions Ocean Engineering 31 2 225 238
    • (2004) Ocean Engineering , vol.31 , Issue.2 , pp. 225-238
    • Lee, T.L.1
  • 15
    • 30044447182 scopus 로고    scopus 로고
    • Neural network prediction of a storm surge
    • T.L. Lee 2006 Neural network prediction of a storm surge Ocean Engineering 33 3-4 483 494
    • (2006) Ocean Engineering , vol.33 , Issue.3-4 , pp. 483-494
    • Lee, T.L.1
  • 16
    • 36148978599 scopus 로고    scopus 로고
    • Back-propagation neural network for the prediction of the short term storm surge in Taichung harbor, Taiwan
    • T.L. Lee 2008 Back-propagation neural network for the prediction of the short term storm surge in Taichung harbor, Taiwan Engineering Applications of Artificial Intelligence 21 1 63 72
    • (2008) Engineering Applications of Artificial Intelligence , vol.21 , Issue.1 , pp. 63-72
    • Lee, T.L.1
  • 17
    • 0037128648 scopus 로고    scopus 로고
    • Application of artificial neural networks in tide forecasting
    • T.L. Lee D.S. Jeng 2002 Application of artificial neural networks in tide forecasting Ocean Engineering 29 9 1003 1022
    • (2002) Ocean Engineering , vol.29 , Issue.9 , pp. 1003-1022
    • Lee, T.L.1    Jeng, D.S.2
  • 18
    • 0035569057 scopus 로고    scopus 로고
    • Development of two artificail neural network methods for landslide susceptibility analysis
    • S. Lee J. Ryu K. Min J. Won 2001 Development of two artificail neural network methods for landslide susceptibility analysis Geoscience and Remote Sensing Symposium 5 2364 2366
    • (2001) Geoscience and Remote Sensing Symposium , vol.5 , pp. 2364-2366
    • Lee, S.1    Ryu, J.2    Min, K.3    Won, J.4
  • 19
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: A review of modelling issues and applications
    • H.R. Maier G.C. Dandy 2000 Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications Environmental Modelling and Software 15 1 101 124
    • (2000) Environmental Modelling and Software , vol.15 , Issue.1 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 20
    • 1842843640 scopus 로고    scopus 로고
    • Improving wave predictions with artificial neural networks
    • O. Makarynskyy 2004 Improving wave predictions with artificial neural networks Ocean Engineering 31 5-6 709 724
    • (2004) Ocean Engineering , vol.31 , Issue.5-6 , pp. 709-724
    • Makarynskyy, O.1
  • 21
    • 33751331476 scopus 로고    scopus 로고
    • Artificial neural networks for wave tracking, retrieval and prediction
    • O. Makarynskyy 2005 Artificial neural networks for wave tracking, retrieval and prediction Pacific Oceanography 3 1 21 30
    • (2005) Pacific Oceanography , vol.3 , Issue.1 , pp. 21-30
    • Makarynskyy, O.1
  • 22
    • 4544314347 scopus 로고    scopus 로고
    • Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia
    • O. Makarynskyy D. Makarynska M. Kuhn W.E. Featherstone 2004 Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia Estuarine Coastal and Shelf Science 61 2 351 360
    • (2004) Estuarine Coastal and Shelf Science , vol.61 , Issue.2 , pp. 351-360
    • Makarynskyy, O.1    Makarynska, D.2    Kuhn, M.3    Featherstone, W.E.4
  • 23
    • 0344689980 scopus 로고    scopus 로고
    • Prediction model for occurrence of impact force
    • H. Mase T. Kianto 1999 Prediction model for occurrence of impact force Ocean Engineering 26 10 949 961
    • (1999) Ocean Engineering , vol.26 , Issue.10 , pp. 949-961
    • Mase, H.1    Kianto, T.2
  • 25
    • 18144423393 scopus 로고
    • Compilation and assessment of geological data for the slope problem
    • Johannesburg
    • Muller, L., Hofman, H., 1970. Compilation and Assessment of Geological Data for the Slope Problem. International Symposium Open Pit Mining, Johannesburg, p.153-170.
    • (1970) International Symposium Open Pit Mining , pp. 153-170
    • Muller, L.1    Hofman, H.2
  • 26
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • D.E. Rumelhart G.E. Hinton R.J. Williams 1986 Learning representations by back-propagating errors Nature 323 6088 533 536
    • (1986) Nature , vol.323 , Issue.6088 , pp. 533-536
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 27
    • 0041112264 scopus 로고
    • Transportation, Res. Board Nat. Ac. Sci., Washington Spee. Rep.
    • Varnes, D.J., 1978. Landslides Analysis and Control. Transportation, Res. Board Nat. Ac. Sci., Washington Spee. Rep., p.176.
    • (1978) Landslides Analysis and Control , pp. 176
    • Varnes, D.J.1
  • 29
    • 62349120794 scopus 로고    scopus 로고
    • An artificial neural network for forecasting the amount of Chinese colliery roadway surrounding rock deformation
    • Y.X. Zhang 1996 An artificial neural network for forecasting the amount of Chinese colliery roadway surrounding rock deformation International Journal of Rock Mechanics and Mining Sciences & Geomechanics 33 5 232A 232A
    • (1996) International Journal of Rock Mechanics and Mining Sciences & Geomechanics , vol.33 , Issue.5
    • Zhang, Y.X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.