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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Changjun Zhu Qin Ju |
| Copyright Year | 2009 |
| Description | Author affiliation: College of Urban Construction, Hebei University of Engineering, Handan, 056038, China (Changjun Zhu) || State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China (Qin Ju) |
| Abstract | At present, classic methods are often used to predict groundwater level, but the result is not ideal. Though GM(1,1) and neural network are applied in this field, some limits have been existed. In view of the difficulty to predict groundwater level, in this paper, a grey system-neural network united model is developed based on the grey theory and neural network method. It predicts various tendency of groundwater 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 dynamic groundwater level analysis. |
| Starting Page | 434 |
| Ending Page | 437 |
| File Size | 252518 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424438174 |
| DOI | 10.1109/ICIMA.2009.5156656 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-15 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mechatronics Statistical analysis Time series analysis united grey ANN Predictive models groundwater level Vectors Least squares approximation neural network Construction industry Neural networks grey model Atmosphere Differential equations prediction |
| Content Type | Text |
| Resource Type | Article |
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