Genetic Algorithm Based on Wavelet Neural Network for the Displacement Prediction of Landslide Conference Paper

abstract

• 2014 IEEE. A method to predict the displacement of landside, genetic algorithm based on wavelet neural network (GAWNN) model, is presented in this paper. The hybrid model improves the predicting precision, which is compared with genetic algorithm based on back-propagation neural network (GABPNN). Furthermore, the hybrid model is applied for predicting the displacement of Baishuihe landslides in the Three Gorges reservoir area of China. The result shows the better accuracy than GABPNN in terms of the same measurements.

name of conference

• 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI)

authors

• Huang, Tingwen

published proceedings

• 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI)

author list (cited authors)

• Jiang, P., Zeng, Z., Chen, J., & Huang, T.

citation count

• 1

complete list of authors

• Jiang, Ping||Zeng, Zhigang||Chen, Jiejie||Huang, Tingwen

publication date

• September 2014

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Genetics

Digital Object Identifier (DOI)

• 10.1109/mfi.2014.6997630

International Standard Book Number (ISBN) 13

• 9781479967322

start page

• 1

end page

• 5