Forecast of regional water resource demand based on back-propagation neural network—taking Jinhua as an example
In order to extend the actual application based on back-propagation (BP) neural network to forecast the regional water resource demand, taking Jinhua as an example, the three types of the main factors of water resource demand in Jinhua were figured out by principal component analysis, which included...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Zhejiang University Press
2011-03-01
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| Series: | 浙江大学学报. 农业与生命科学版 |
| Subjects: | |
| Online Access: | https://www.academax.com/doi/10.3785/j.issn.1008-9209.2011.02.017 |
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| Summary: | In order to extend the actual application based on back-propagation (BP) neural network to forecast the regional water resource demand, taking Jinhua as an example, the three types of the main factors of water resource demand in Jinhua were figured out by principal component analysis, which included dynamic changes of economy, improvement of the water resource exploring and serious pollution of water resources. To predict the water resource demand in the region, BP neural network model was applied. Through the network learning and training, the total water resource demand in Jinhua would reach to 21.935 280×10<sup>8</sup> m<sup>3</sup> in 2010. It can provide some reference to build a plan of the regional development which is coordinated with the water resources. |
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| ISSN: | 1008-9209 2097-5155 |