Title :
Predication of Landslide Based on Grey System and Evolutionary Artificial Neural Networks
Author_Institution :
Wuhan Polytech. Univ., Wuhan, China
Abstract :
Predication of landslide is very important in control of landslide disaster. Considering the monotonously increasing character of time series of the landslide displacement, a new intelligent method combining Grey System and Evolutionary Neural Network (ENN) is proposed here. In this method, based on the principles of displacement decomposition, the trend of time series is extracted by Grey System and the deviation is approximated by the new ENN proposed here. In this new ENN, the architecture and algorithm parameters can evolve simultaneously through combining modified BP algorithm and Immunized Evolutionary Programming proposed by author. This new method is applied in the Xintan landslide, and the results show that the generalization of the new method is good and it can predict the landslide very well.
Keywords :
backpropagation; disasters; evolutionary computation; grey systems; neural nets; time series; BP algorithm; Xintan landslide; displacement decomposition; evolutionary artificial neural network; evolutionary programming; grey system; landslide disaster; landslide displacement; time series; Artificial neural networks; Displacement measurement; Evolutionary computation; Forecasting; Neurons; Terrain factors; Time series analysis; Evolutionary neural networks; Grey system; Landslide; Predication;
Conference_Titel :
System Science, Engineering Design and Manufacturing Informatization (ICSEM), 2010 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8664-9
DOI :
10.1109/ICSEM.2010.106