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

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=232011