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1.
A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH4+-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m3/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH4+-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH4+-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH4+-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R2) and lower root mean squared errors (RMSE) values. 相似文献
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Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong 总被引:4,自引:0,他引:4
As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NOx and NO2 are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NOx and NO2 concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NOx and NO2 concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods. 相似文献
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江西九岭地体南缘武功山地体北侧以及其间的萍乐盆地内,有大量的逆冲推覆构造分布。逆冲推覆构造的类型有两种──逆冲推覆型和重力滑覆型。逆冲推覆构造具有横向上对冲挤压,纵向上多层滑动的特征,据此笔者建立了一个可能的多层滑动──对冲挤压模式,并根据地质和同位素年龄资料讨论了逆冲推覆构造的演化历史,指出区内大规模逆冲推覆构造的形成时间为中生代晚期(119.6Ma)。 相似文献
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对细密沟槽铝合金挤压件的结构进行了分析,研究和探讨了该类冷挤压件的成形过程。通过对挤压过程中金属的流动,以及模具的受力分析和模具结构的改进,解决了该类零件在挤压过程中上模的断齿问题。 相似文献
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对塑料瓶的电磁成形封接工艺进行研究,通过对放电电压、电容、线圈位置等参数进行调节,得出了优化的封口工艺。试验结果表明线圈位置,电压对封口效果影响较大。 相似文献
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介绍了多点成形技术、激光成形技术、冲压智能化技术、成形过程的计算机仿真技术等几种柔性化程度高的板材成形新技术及其发展趋势 相似文献
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