| An improved BP neural network based on evaluating and forecasting model of water quality in Second Songhua River of China |
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| 引用本文： | Bin ZOU Xiaoyu LIAO Yongnian ZENG Lixia HUANG. An improved BP neural network based on evaluating and forecasting model of water quality in Second Songhua River of China[J]. 中国地球化学学报, 2006, 25(B08): 167-167 |
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| 作者姓名： | Bin ZOU Xiaoyu LIAO Yongnian ZENG Lixia HUANG |
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| 作者单位： | [1]School of Environment and Chemical Engineering of Yanshan University, Qing- Huangdao 066004, China [2]Institute of RS and GIS in Northeast Normal University, Changchun 130024, China |
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| 摘 要： | Taking the Second Songhua River which lies in the northeast of China as a study area, this paper firstly designs the improved BP neural network water evaluating and forecasting model of which 13 water evaluating items are selected as nodes in input layer; 6 classes of evaluating results are selected as nodes of output layer; then, with the ＂0, 1＂ identified pattern and continually practiced comparisons, ＂13-9-5-6＂ double hidden layers with optimized training structure are confirmed; on the basis of this work, the water quality of the Second Songhua River was evaluated and forecasted at the end. The results showed that in the six classes of predefined water quality in 157 stations, none of them belongs to class Ⅰ, and classes Ⅱ, Ⅲ, Ⅳ and Ⅴ are as follows： 8.91%, 58.59%, 18.47%, 1.91% and 12.1%, respectively; the precision of these evaluating and forecasting results is 82.8%.
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| 关 键 词： | 河流 水质 人工神经网络 水文化学 |
An improved BP neural network based on evaluating and forecasting model of water quality in Second Songhua River of China |
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| Abstract: | |
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| Keywords: | Second Songhua River water quality evaluating and forecasting model BP neural network |
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