The wavelet multilayer perceptron for the prediction of earthquake time series data

Ali , Ashikin and Ghazali, Rozaida and Mat Deris, Mustafa (2011) The wavelet multilayer perceptron for the prediction of earthquake time series data. In: Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services (iiWAS '11), 5-7 December 2011, Ho Chi Minh City, Vietnam.

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Abstract

Forecasting a time series is a common problem in many domains of science, and this has been addressed for a long time by scientists. There exist many techniques to pre-process time series, and chief among them is wavelet approach. The use of wavelet technique to pre-process time series data has been proven to overcome the problems in numerous application where the data are imbalanced due to the outliers and noise that discriminates the data. In this work, we proposed a new model which makes use the wavelet technique to pre-process the time series data before feeding to the MLP, and it is called a wavelet multilayer perceptron (W-MLP). The model has been trained and tested for the prediction of California earthquake data. Simulation results on the prediction of earthquake time series show that W-MLP performs considerably better results when compared to Multilayer perceptron (MLP) in terms of the prediction error.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:multilayer perceptron; wavelet; pre-processing; outliers
Subjects:Q Science > QA Mathematics > QA297 Numerical analysis. Analysis
Divisions:Faculty of Computer Science and Information Technology > Department of Software Engineering
ID Code:2983
Deposited By:Normajihan Abd. Rahman
Deposited On:22 Jan 2013 18:31
Last Modified:21 Jan 2015 15:12

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