Landslide Deformation Prediction Based on Recurrent Neural Network

[1]  Wen Yu,et al.  Two Types of Haar Wavelet Neural Networks for Nonlinear System Identification , 2012, Neural Processing Letters.

[2]  Xiuzhen Li,et al.  Landslide displacement prediction based on combining method with optimal weight , 2012, Natural Hazards.

[3]  Th.W.J. van Asch,et al.  Triggering conditions and depositional characteristics of a disastrous debris flow event in Zhouqu city, Gansu Province, northwestern China , 2011 .

[4]  Matteo Matteucci,et al.  Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba , 2011, Comput. Geosci..

[5]  Çagdas Hakan Aladag,et al.  Forecast Combination by Using Artificial Neural Networks , 2010, Neural Processing Letters.

[6]  Shi-Sheng Li,et al.  Study on deformation prediction of landslide based on genetic algorithm and improved BP neural network , 2010, Kybernetes.

[7]  R. Jibson Regression models for estimating coseismic landslide displacement , 2007 .

[8]  Manoj K. Arora,et al.  A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas , 2006 .

[9]  Wen Yu,et al.  State-Space Recurrent Fuzzy Neural Networks for Nonlinear System Identification , 2005, Neural Processing Letters.

[10]  Hongbo Zhao,et al.  Modeling non-linear displacement time series of geo-materials using evolutionary support vector machines , 2004 .

[11]  K. Neaupane,et al.  Use of backpropagation neural network for landslide monitoring: a case study in the higher Himalaya , 2004 .

[12]  Thomas W. Kirchstetter,et al.  Emissions From Miombo Woodland and Dambo Grassland Savanna Fires in Southern Africa , 2003 .

[13]  P. Lu,et al.  Artificial Neural Networks and Grey Systems for the Prediction of Slope Stability , 2003 .

[14]  J. V. Andersen,et al.  Towards landslide predictions: two case studies , 2003, physics/0305067.

[15]  D. Sornette,et al.  Slider block friction model for landslides: Application to Vaiont and La Clapière landslides , 2002, cond-mat/0208413.

[16]  Duc Truong Pham,et al.  Training Elman and Jordan networks for system identification using genetic algorithms , 1999, Artif. Intell. Eng..

[17]  Dervis Karaboga,et al.  Training recurrent neural networks for dynamic system identification using parallel tabu search algorithm , 1997, Proceedings of 12th IEEE International Symposium on Intelligent Control.

[18]  K. Mehrotra,et al.  Nonlinear system identification using recurrent networks , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.

[19]  B. Voight,et al.  A Relation to Describe Rate-Dependent Material Failure , 1989, Science.

[20]  Zhang Maosheng TRIGGERING FACTORS AND FORMING MECHANISM OF LOESS LANDSLIDES , 2011 .

[21]  Leng Wuming,et al.  Nonlinear Combination Predicting Based on Support Vector Machines for Landslide Deformation , 2007 .

[22]  Huang Run-qiu,et al.  LARGE-SCALE LANDSLIDES AND THEIR SLIDING MECHANISMS IN CHINA SINCE THE 20TH CENTURY , 2007 .

[23]  Li Yawei,et al.  APPLICATION OF GREY-NEURAL NETWORK MODEL TO LANDSLIDE DEFORMATION PREDICTION , 2007 .

[24]  Wen Yu,et al.  Nonlinear system identification using discrete-time recurrent neural networks with stable learning algorithms , 2004, Inf. Sci..

[25]  John J. Grefenstette,et al.  Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.