DocumentCode :
232011
Title :
Genetic Algorithm based Neural Network for the displacement of landslide forecasting
Author :
Jiejie Chen ; Zhigang Zeng ; Ping Jiang ; Huiming Tang
Author_Institution :
Sch. of Autom., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
5013
Lastpage :
5016
Abstract :
This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Network (GA-BPNN). A case study of Yuhuangge landslide in the Three Gorges reservoir in China is used to illustrate the capability and merit of our schemes. In addition, the result shows that GP-BPNN get better accuracy than GA-RBFN in the same measurements.
Keywords :
backpropagation; genetic algorithms; geomorphology; geophysics computing; radial basis function networks; China; GA-BPNN; GA-RBFN; Three Gorges reservoir; Yuhuangge landslide; backpropagation neural network; genetic algorithm; hybrid prediction models; landslide displacement; radial basis function neural network; Educational institutions; Forecasting; Genetic algorithms; Neural networks; Terrain factors; Training; Transfer functions; Displacement; GA-BPNN; GA-RBFN; Prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6895791
Filename :
6895791
Link To Document :
بازگشت