Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

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.     

淹水时间对土壤粘闭的影响

本文研究了植稻前淹水时间长短对土壤物理性质和粘闭作用的影响。结果表明,淹水可以显著地降低土壤强度,但土壤抗穿透力并不随淹水时间的延长而进一步明显下降;延长淹水时间,可以促进土壤粉粒和粘粒的分散,但土壤粘闭胼形成的有效粘闭层厚度以及粘闭后表层土壤强度的降低、主要受所使用的粘闭机具的影响,而与淹水时间的长短无关。因此,过分地延长淹水时间的措施,在生产实践上的意义并不大。     

典型西南工业城市春冬季PM2.5来源与潜在源区分析——以柳州市为例

为了揭示柳州城区春冬季PM_2.5的来源及其潜在源区分布和贡献,利用2018年24h自动监测数据和气象数据对柳州市大气污染物浓度变化特征进行了分析,并且使用后向轨迹模型（HYSPLIT）对春冬季柳州市PM_2.5逐日72h气流后向轨迹和前向轨迹进行聚类分析,同时结合潜在源贡献因子分析法（WPSCF）和轨迹浓度权重法（WCWT）对其潜在源区和浓度贡献进行了分析.结果显示,（1）在研究期内,不利的主导风向和工业区布局导致研究区PM_2.5在春冬季污染较严重,且工业源和交通源是其主要本地来源;（2）春冬季PM_2.5高值主要来源于西北和东南方向,其中,西北向PM_2.5主要来源于本地排放,且浓度在空间上呈现西高东低的趋势;（3）春季后向轨迹PM_2.5浓度整体大于冬季,春冬季中对柳州市PM_2.5影响最大轨迹均来自东部的短距离输送,而来自西北的气流轨迹输对PM_2.5贡献最低.春冬季柳州市大气PM_2.5通过气流传输对贵州地区大气环境有较大影响;（4）春季,柳州市PM_2.5的主要潜在源区分布在广西东南部、广东中西部、南海沿岸海域、湖南中部、江西西北部、湖北东部及安徽西北部;冬季,主要分布在广西东南部、广东西南部和南海沿岸海域.     

颗粒物分界层Mie散射激光雷达识别的sigmoid算法

基于成都市2013年6月~2015年5月期间由Mie散射激光雷达探测的大气消光系数廓线资料,发现混合层以上在颗粒物消光和分子消光之间一致存在一个S型的过渡区,利用sigmoid函数对此分布形态进行模拟,通过计算该函数上下曲率最大点所在的高度,据此提出了颗粒物分界层Mie散射激光雷达识别的sigmoid算法.针对该算法模拟效果的分析表明,颗粒物分界层过渡区附近大气消光系数理论廓线和实测廓线保持了高度的相关性,二者在春夏秋冬四季的相关系数（R）分别为0.9971±0.0052、0.9935±0.0167、0.9979±0.0038和0.9990±0.0021（均通过α=0.05的显著性检验）.基于sigmoid算法计算的颗粒物分界层过渡区与成都市温江站探空资料得到的逆温层之间存在很好的对应关系.     

A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

新疆生态功能区划初探

“新疆生态功能区划”参考了“中国综合生态环境区划方案”，以《生态功能区划暂行规程》为依据，充分考虑新疆独特的地理分布格局，将新疆分为5个生态区，18个生态亚区，79个生态功能区。“新疆生态功能区划”对科学有效地管理新疆生态环境，因地制宜地实施保护和治理策略，保证社会经济可持续发展具有重要意义。     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

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 NO_x 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, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x 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.     

太湖水质氮素质量浓度时空差异特征及影响因素分析

通过对2014—2016年湖体水质中氮素质量浓度分析,结合出入湖总氮浓度、水量、湖体水生生态等影响因素,发现太湖水体中总氮浓度呈现逐年下降的趋势,各监测点位总氮为0.530 mg/L～5.51 mg/L,时空分布不均,差异明显。时间上,总氮浓度表现为春季最高,夏季和秋季最低,且月均值变化曲线呈现出规律的正弦函数波形。空间上,总氮浓度大致表现出由西部湖区向东部湖区递减的趋势,呈现西部湖区﹥北部湖区﹥南部湖区﹥湖心区﹥东部湖区。要改善湖体水质,不仅要切断污染源,而且要加强水生生态功能修复。     

曲面零件在拉深过程中内皱时刻及影响因素

进一步推导了曲面零件悬空区上的应力分布及临界失稳公式。然后通过计算机编程 ,求解了临界失稳方程 ,得到了拉深系数、相对锥顶半径、相对圆角半径、材料相对厚度与临界失稳时刻间的关系曲线 ,并对曲线变化的规律进行了分析。     

花岗岩类岩体与金矿床成因关系的探讨

花岗岩类岩体与金矿床存在着密切的空间联系，其成因关系一直是矿床学界争论的焦点，目前传统的岩浆热液成因观点仍居统治地位。随着地质资料的积累，高温高压实验技术，尤其是金矿床同位素定年技术的进展，传统观点受到了严峻挑战。成岩成矿的时代与时差、成矿流体的来源和成矿物质的来源等确定金矿床成因类型关键因素的综合研究表明，有密切空间关系的金矿床与花岗岩类岩体之间，在多数情况下两者并无直接的成因联系，金矿床不是岩浆热液成因，而是与大气降水或建造水有关的改造成矿作用的产物。