| 应用神经网络对地下水反硝化效果预测与验证 |
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| 引用本文： | 左金龙.应用神经网络对地下水反硝化效果预测与验证[J].环境科学与管理,2010,35(6):186-189. |
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| 作者姓名： | 左金龙 |
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| 作者单位： | 哈尔滨商业大学环境工程系,黑龙江,哈尔滨,150076 |
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| 摘 要： | 应用人工神经网络对生物脱氮工艺进行预测并验证。采用工艺参数如COD、NO3-N、NO2-N、DO等作为输入节点，COD、NO3-N作为输出节点。结果显示神经网络能够较好地预报出水的水质参数。出水硝酸盐和COD预测结果与试验结果符合得较好，相对误差分别在10％和5％范围内。
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| 关 键 词： | 神经网络 地下水 脱氮 |
Prediction and Verification of Groundwater Denitification by Artificial Neural networks |
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| Zuo Jinlong.Prediction and Verification of Groundwater Denitification by Artificial Neural networks[J].Environmental Science and Management,2010,35(6):186-189. |
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| Authors: | Zuo Jinlong |
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| Institution: | Zuo Jinlong (Department of Environmental Engineering, Harbin University of commerce, Harbin 150076, China) |
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| Abstract: | The artificial neural networks（ ANN ）was applied in denitrification process in ground water and this prediction and verification of this process were investigated. The parameters such as COD, NO3 - N, NO2 - N, DO has been used for input, whereas the nitrate and COD used for output. The experimental results show that the ANN is able to predict the output water quality parameters very well - including nitrate as well as nitrite and COD. Most of relative error of NO3 - N and COD were in the range of ±10% and ±5% respectively. |
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| Keywords: | artificial neural networks groundwater denitrification |
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