Paper Title:
Forecasting Groundwater Level Based on Wavelet Network Model Combined with Genetic Algorithm
  Abstract

This paper proposed an improved wavelet network model (WNM) which combined with genetic algorithm (GA) to forecast groundwater level, GA is used to determine the weights and parameters of WNM, which can avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models. Compared to WNM, our results show that the GA-WNM predictor can reduce significantly both relative mean errors and root mean squared errors of predicted groundwater level. We demonstrate the feasibility of applying GA-WNM in groundwater level prediction and prove that GA-WNM is applicable and performs well for groundwater data analysis.

  Info
Periodical
Advanced Materials Research (Volumes 113-116)
Edited by
Zhenyu Du and X.B Sun
Pages
195-198
DOI
10.4028/www.scientific.net/AMR.113-116.195
Citation
L. Y. Wang, W. G. Zhao, "Forecasting Groundwater Level Based on Wavelet Network Model Combined with Genetic Algorithm", Advanced Materials Research, Vols. 113-116, pp. 195-198, 2010
Online since
June 2010
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Price
$32.00
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