A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Multiple neural networks switched prediction for landslide displacement
Abstract An accurate prediction of landslide displacement is challenging and of great interest to governments and researchers. In order to reduce the risk of selecting the types of influencing factors and artificial neural networks (ANNs), a multiple ANNs switched prediction method is proposed for landslide displacement forecasting. In the first stage, a set of individual neural networks are developed based on different environmental factors and/or different training algorithms. In the second stage, a switched prediction method is used to select the appropriate individual neural network for prediction purpose. For verification and testing, three typical landslides in Three Gorges Reservoir, namely Baishuihe landslide, Bazimen landslide and Shiliushubao landslide, are presented to test the effectiveness of our method. Application results demonstrate that the proposed method can significantly improve model generalization and perform similarly to, or better than, the best individual ANN predictor.
Highlights A set of predictors considering different environmental factors are established. A switched method is proposed to select the appropriate individual predictor. Three typical landslides are presented to illustrate the capability of the method.
Multiple neural networks switched prediction for landslide displacement
Abstract An accurate prediction of landslide displacement is challenging and of great interest to governments and researchers. In order to reduce the risk of selecting the types of influencing factors and artificial neural networks (ANNs), a multiple ANNs switched prediction method is proposed for landslide displacement forecasting. In the first stage, a set of individual neural networks are developed based on different environmental factors and/or different training algorithms. In the second stage, a switched prediction method is used to select the appropriate individual neural network for prediction purpose. For verification and testing, three typical landslides in Three Gorges Reservoir, namely Baishuihe landslide, Bazimen landslide and Shiliushubao landslide, are presented to test the effectiveness of our method. Application results demonstrate that the proposed method can significantly improve model generalization and perform similarly to, or better than, the best individual ANN predictor.
Highlights A set of predictors considering different environmental factors are established. A switched method is proposed to select the appropriate individual predictor. Three typical landslides are presented to illustrate the capability of the method.
Multiple neural networks switched prediction for landslide displacement
Lian, Cheng (author) / Zeng, Zhigang (author) / Yao, Wei (author) / Tang, Huiming (author)
Engineering Geology ; 186 ; 91-99
2014-11-26
9 pages
Article (Journal)
Electronic Resource
English
Multiple neural networks switched prediction for landslide displacement
| British Library Online Contents | 2015
Multiple neural networks switched prediction for landslide displacement
| Online Contents | 2015
Displacement Prediction of Jiuxianping Landslide Using GRU Networks
| Springer Verlag | 2023
Landslide displacement prediction by using Bayesian optimization–temporal convolutional networks
| Springer Verlag | 2024
Landslide displacement prediction by using Bayesian optimization–temporal convolutional networks
| Springer Verlag | 2024