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.     

人工神经网络模型和公路复垦土地适宜性评价

提出了人工神经网络用于公路临时用地复垦土地适宜性评价，利用该模型对京大高速公路山西段复垦山西段复垦土地进行了适宜性评价，探讨了人工神经网络在土地复垦适宜性评价时的特点和注意问题。     

企业计算机网络与系统安全

本文介绍了网络技术与系统的内在结构以及各个环节可能存在的安全漏洞，分别对如何提高局域网，广域网，外部网和系统的安全性进行分析，提出了相应的解决办法。     

供水管线震害量化参数--渗漏面积的估算方法

为了分析管线破坏状态对震后供水管网功能的影响，首先需要对管线的震害状态进行量化。建议用管线渗漏面积标定管线的破坏状态。在管线震害分析和理论计算的基础上，提出了震后管线渗漏面积的计算方法，为进一步进行供水管网抗震分析和设计提供了研究基础。     

City hazardous gas monitoring network

In our today's societies, many dangerous chemicals are produced and transported. Due to the vast use of chemicals, more chemical accidents are taking place with huge losses. In this study a city hazardous gas monitoring network was designed to detect the dispersion of toxic and combustible gases in the primary stages. The network could cover hazardous chemical facilities, important hazardous chemical routes, warehouses and special locations which may be the targets of terrorist attacks. The network is consisted of several local networks and a central control panel complex. Each local network has a local control panel in the center and many detectors and sounders around it at distances less than 3000 m that communicate with the local control panels wirelessly. In each location there are two types of gas detectors, toxic and combustible, and a sounder which are equipped with a wireless, radio frequency modem allowing the units to communicate readings and other information on a real-time basis with a remotely located local control panel. High sensitive Photo Ionization Detectors, PIDs, are used to provide fast and low-level on-site screening for chemicals contamination. Combustible gas detectors are the second choice to sense the combustible gas and verify the readings of PIDs in this regard. The central panel consists of several connected control panels work uniquely helping a computer set and the appropriate software and communicate with local control panels via telephone lines. All of the network components are shown on the monitor of central panel with special symbols by geographical information system program. The system is fully addressable so that the high level detection of a detector produces a blinking color double-circle around its symbol in GIS plan. In case of high level gas detection, a team of experts who are fully equipped with different portable detectors depart to the site to test the field to identify the chemicals. All readings of detectors are saved in a data bank and then analyzed to find any chemicals spills and leakages. The network was simulated by a special program so that the components of local networks and the central panel are shown in separate windows. By clicking on one detector on environmental window the formerly designed responses will be activated in central panel window.     

完善应急监测网络提高环境管理能力

阐述了建立广东省环境应急监测网络的重要性,以及加大对环境应急监测网络建设投入、配套信息系统及公告制度建设的要求、方法、程序,并从完善应急监测网络,建立应急监测法规体系,加强应急监测队伍建设等方面对广东省环境应急监测体系的发展方向进行了探讨。     

环境监测站INTRANET建设研究

研究探讨了环境监测站内部网络 (Intranet)建设方案、Web数据库开发应用方案、网站的规划方法、结构与内容 ,对其经济性、技术合理性、适用性作了阐述。     

A methodological framework for improving air quality monitoring network layout. Applications to environment management

This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network (AQMN). It requires to be constituted by a minimum and reliable number of measurement sites. Nevertheless, the AQMN efficiency should be assessed over time, as a consequence of the possible emergence of new emission sources of air pollutants, which could lead to variations on their spatial distribution within the target area. PM₁₀ particles data monitored by the Community of Madrid's (Spain) AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance. The annual spatial distribution of average PM₁₀ levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system (GIS), and the percentage of similarity between both postulates was quantified using simple linear regression (> 95%). As one innovative tool of this study, the practical application of the proposed methodology was validated using PM₁₀ particles data measured by AQMN during 2007 and 2018, reaching a similitude degree higher than 95%. The influence of temporal variation on the proposed methodological framework was around 20%.The proposed methodology sets criteria for identifying non-redundant stations within AQMN, it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations, which could help to tackle efforts to improve the air quality management.     

SDS促进复配酶水解排水管网沉积物

采用SDS协同复配酶水解排水管网沉积物,分别考察了SDS投加量、反应时间、pH、温度4个影响因素对沉积物水解效果的影响,并通过 SEM、EPS、三维荧光光谱以及粒径等表征方法进行机理分析。结果表明,投加5%(w:w)SDS与8%(w:w)复配酶,在原泥pH(7.28±0.3)、25 ℃、反应时间为2 h时,沉积物水解效果最好。此时SCOD、多糖和氨氮分别由初始的5 686.9、1 913.75和87.32 mg·L⁻¹增加到8 192.9、3 561.29和153.37 mg·L⁻¹,有机质含量由56.32%下降到55.59%。在SDS+复配酶处理管网沉积物后,其内部紧实结构被破坏,TB-EPS向S-EPS转移,腐殖酸类物质荧光强度增强,表明溶解性EPS增多,且沉积物粒径向<300 μm转变。高通量测序分析结果表明,SDS+复配酶对管网沉积物微生物种类的丰富度和多样性影响不大,但在一定程度上会改变微生物的功能菌群,减少CH₄和H₂S的产生。以上研究结果可为延缓排水管网淤堵问题提供数据支持。     

变权组合模型在景观水体水质模拟中的应用

针对景观水体的水质模拟与预测问题,在BP神经网络和支持向量机模型的基础上,建立了权重随输入量变化的变权组合模型。该模型既能充分利用各个单一模型的优点,又能避免固定权重分配的弊端。经实例验证,与单一的BP神经网络和支持向量机模型相比,变权组合模型拟合精度更高,预测结果更为准确。