Title :
Groundwater quality forecast using ARMA and GM model
Author :
Zhu, Changjun ; Wu, Liping
Author_Institution :
Coll. of Urban Constr., Hebei Univ. of Eng., Handan, China
Abstract :
In view of the defect that the grey method can only predict the tendency approximately and artificial neural network can not predict the future tendency really, a new combined grey neural network model was proposed. This paper mainly analyses the groundwater quality and establishes their mathematical model based on the groundwater monitoring data of one area by combined grey neural network method. It predicts various tendency of groundwater quality in this area in the future. Case study indicates that precision of the model is rather high and its popularization significance is better than the other models, and has some practical value when being used in the prediction of groundwater quality analysis.
Keywords :
autoregressive moving average processes; forecasting theory; grey systems; groundwater; neural nets; water quality; ARMA model; GM model; grey neural network; groundwater quality forecast; Artificial neural networks; Computational intelligence; Equations; Neural networks; Predictive models; Stochastic processes; Stochastic resonance; Time series analysis; Water resources; Yttrium; BP neural network; combined grey neural network; grey prediction; groundwater quality;
Conference_Titel :
Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4606-3
DOI :
10.1109/PACIIA.2009.5406556