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515825903931银虫 (正式写手)
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10金币求助翻译润色
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摘要如下，软件翻译拒绝 基于神经网络的传爆药废水COD去除率预测研究 摘要：为预测超临界水氧化法处理二硝基重氮酚生产废水的COD（chemicalo xygen demand）去除率，采用HXDK-01-A间歇式超临界水氧化实验装置处理实际工业生产废水，主要考察反应温度、反应压力、停留时间和过氧量对COD去除率的影响。采用实验数据，以反应温度、反应压力、停留时间和过氧量为网络输入，COD去除率为网络输出，以Matlab为平台建立了Elman神经网络预测模型。神经网络模型预测的均方差为0.0418，单个最大误差为-0.3231，最小误差为0.0296；多元回归分析拟合数据的均方差为0.3149，单个最大误差为0.8830，最小误差为0.2200，神经网络预测结果明显优于多元回归分析结果。说明采用神经网络模型预测超临界水氧化法的废水COD去除率是可行的。 关键词：环境科学；超临界水氧化；二硝基重氮酚；Elman神经网络；废水处理 Elman Model in The Prediction of The COD Removal Rate of The Booster explosive wastewater Abstract: In order to predict the COD (chemical oxygen demand)removal rate of the DDNP wastewater which was carried out by supercritical water oxidation(SCWO), uses the HXDK-01-A intermittence type supercritical water oxidation device deal with the actual industrial production wastewater, main inspection reaction temperature,reaction pressure,residence time,oxygen excess to COD removal rate influence. Using experimental data,a single hidden layer Elman prediction model is established using the reaction temperature,reaction pressure,residence time,oxygen excess as input variables,the COD removal rate as output. The MSE of the Elman model is 0.0418,the biggest error is - 0.3231, the least error is 0.0296;compared with Elman model, the MSE of the multiple regression is 0.3149, he biggest error is 0.8830, the least error is 0.2200,the Elman Neural network prediction results are better than the results of multiple regression analysis.The result shows that the Elman model can be adopted to the prediction of the COD removal rate of the wastewater carried out by SCWO. Key words:Supercritical water oxidation;Diazodinitrophenol;Elman neural network;wastewater treatment |
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myhaoqq
铁杆木虫 (著名写手)
小木虫警备司令员
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2楼2009-04-22 21:25:36
515825903931
银虫 (正式写手)
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3楼2009-04-22 21:44:40
myhaoqq
铁杆木虫 (著名写手)
小木虫警备司令员
- 翻译EPI: 1
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515825903931(金币+10,VIP+0): 4-22 22:08
515825903931(金币+10,VIP+0): 4-22 22:08
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The prediction for the COD removal rate of The booster explosive wastewater based on Elman neural network Abstract: In order to predict for the COD (chemical oxygen demand) removal rate of the DDNP wastewater carried out by supercritical water oxidation(SCWO), the HXDK-01-A Interval supercritical water oxidation device was used to dispose the actual industrial production wastewater, reaction temperature,reaction pressure,residence time,oxygen excess were inspected for the influence of COD removal rate. Employing experimental data, a single hidden layer Elman prediction model was established by the reaction temperature,reaction pressure,residence time,oxygen excess as input variables,the COD removal rate as output.The MSE of the Elman model is 0.0418,the biggest error is - 0.3231, the least error is 0.0296; the MSE of the multiple regression is 0.3149, he biggest error is 0.8830, the least error is 0.2200, compared with the multiple regression, ,the prediction result of the Elman Neural network was better. The result illuminated that the Elman model can feasible for the prediction of the COD removal rate of the wastewater performed by SCWO. Key words:environmental science; Supercritical water oxidation; Diazodinitrophenol; Elman neural network; wastewater treatment 改好了，感觉实验文章应该用被动态和过去时比较好 |
4楼2009-04-22 21:52:12
515825903931
银虫 (正式写手)
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5楼2010-03-29 09:07:15
