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.     

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.     

环境监测业务管理系统的设计与开发

以郑州市环境监测中心站监测业务流程为例,从技术路线、系统结构设计、系统功能分析和技术实现等方面分析并介绍了环境监测业务管理系统的特点和开发时需解决的技术问题。探讨了建立基于B/S结构、J2EE技术架构、创新的组件装配方式、Oracle9i数据库、中间件和多层体系结构等多项先进技术进行系统实现的设计方案。     

浅谈小型餐饮服务业排污申报登记

简述了小型餐饮服务业的特点，指出排污申报登记制度落实难、废水中各污染物排放量核定难及申报登记表设计欠合理是小型餐饮服务业在排污申报登记中存在的主要问题。提出，应加大宣传力度，进一步提高餐饮服务业业主以及广大公民的环保意识；制定较合理的排污量核算系数，修订申报内容；实行《排污申报登记注册证》制度，强化执法力度，以促进小型餐饮服务业全面实施排污申报登记制度。     

生态系统服务的核算方法

生态系统服务是指对人类生存及生活质量有贡献的生态系统产品和生态系统功能 ,包括由自然生态过程产生并维持的环境和资源条件。目前已有的生态系统服务核算方法可以分为市场价值法、替代市场法和假想市场法。     

Developing Canada's National Forest Carbon Monitoring, Accounting and Reporting System to Meet the Reporting Requirements of the Kyoto Protocol

The rate of carbon accumulation in the atmosphere can be reduced by decreasing emissions from the burning of fossil fuels and by increasing the net uptake (or reducing the net loss) of carbon in terrestrial (and aquatic) ecosystems. The Kyoto Protocol addresses both the release and uptake of carbon. Canada is developing a National Forest Carbon Monitoring, Accounting and Reporting System in support of its international obligations to report greenhouse gas sources and sinks. This system employs forest-inventory data, growth and yield information, and statistics on natural disturbances, management actions and land-use change to estimate forest carbon stocks, changes in carbon stocks, and emissions of non-CO₂ greenhouse gases. A key component of the system is the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS). The model is undergoing extensive revisions to enable analyses at four spatial scales (national, provincial, forest management unit and stand) and in annual time steps. The model and the supporting databases can be used to assess carbon-stock changes between 1990 and the present, and to predict future carbon-stock changes based on scenarios of future disturbance rates and management actions.     

餐饮娱乐业的环境污染与综合防治

主要分析了城市餐饮娱乐业环境污染的几个方面,针对我国目前现状,从政策法规、行政管理、技术改造等方面提出了一些综合防治对策。     

我校设置税务代理专业的可行性研究

本文针对当前社会对税务代理人员的旺盛需求,结合我校现有的教学资源,对在我校开设税务代理专业的可行性进行了研究与分析。     

会计电算化对内部审计的影响

随着网络环境下会计电算化管理系统的应用,传统的审计模式、工作方法已不能满足新形式下内部审计的需要。本文在论述电算化会计系统的发展历程的基础上,阐述了会计电算化对内部审计所带来的制约和影响,提出了会计电算化环境下,内部审计工作的工作重点。     

会计集中核算的实践与思考

会计集中核算是会计管理体制改革的一项举措,从试点单位初步运行情况看,其作用明显,产生了较好的社会效益和经济效益,为防止各种违纪行为筑起了一道坚固的防线。虽然会计集中核算有一定的局限性,但它作为会计管理体制改革的一项有益尝试,应在有条件的部门积极推行