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.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

发挥环境保护档案在突发性环境污染事件中的重要作用

环境保护档案是环境状况的历史记录,是环境保护成果及科技信息的载体。在环境形势十分严峻的今天,环境保护部门要充分发挥环保档案的信息潜能,变被动的、低档次、知识审查服务,为积极主动的、高层次、超前的知识配送服务,为政府及时处理突发性环境污染事件提供科学依据。     

森林火灾分区分类施治理论的灾害学基础

森林火灾是当今世界上八大自然灾害之一,不仅具有灾害学中所描述的关于自然灾害的一般特性,而且具有自身的特点.本文从自然灾害的属性、特点、基本研究内容和方法等几个方面,论述了灾害学为森林火灾分区分类施治理论提供的理论依据.     

清洁生产理论基础

重点分析了清洁生产的物流基础、价值基础、经济基础,并与末端治理对比,从而论证了清洁生产是实现经济效益和环境效益的最佳模式,是实现可持续发展的必然选择。     

基于径向基函数神经网络方法的城市生态压力预测

针对城市生态压力影响因素复杂,难以对城市未来可持续发展状况做出准确判断的问题,提出了城市生态压力的径向基函数神经网络预测模型,分析了影响城市生态系统的主要因素.以抚顺市1995-2009年数据为基础,验证了模型的准确性并预测了该市2010-2015年城市生态系统的压力情况.研究结果表明:能源消耗指标是影响城市生态系统压力的主要因素;运用径向基函数神经网络模型对训练样本的拟合精度以及对测试样本的仿真精度分别达97.91%和94.16%;抚顺市2015年的人均生态足迹、 生态承载力和生态赤字分别达到7.013、 0.523和6.49 hm²/人.     

经济发展成本分析:可持续发展经济学的理论基础

可持续发展战略存在着理论与实践上的严重反差，其主要原因是可持续发展经济缺乏统一的理论基础，本文通过对经济学不同流派关于可持续发展问题研究的评析，认为可持续发展经济学需要建立一个统一的理论基础，并提出经济发展成本分析是可持续发展经济学的理论基础，围绕这一理论基础对可持续发展的概念进行了重新界定，并主张要把制度的激励与约束以及政策的引导纳入可持续发展经济途径研究的视野之中。     

RBF神经网络可靠度分析方法在边坡稳定性研究中的应用

针对边坡稳定性可靠度分析,当状态函数无法显式表达且传统计算方法求解复杂问题困难时,提出一种基于ABAQUS和粒子群优化径向基函数神经网络的可靠度分析方法。基于ABAQUS的强度折减方法计算所选随机变量对应的安全系数,利用径向基函数神经网络的数据拟合功能,建立模型并映射出安全系数和随机变量之间的关系,构造响应面功能函数;利用蒙特卡罗生成的大量随机样本代入功能函数得到相应的安全系数,进而计算边坡的失稳概率和可靠度指标来反映边坡稳定性。研究结果表明:相对于传统方法,本文方法计算效率更高、误差更小,适合实际工程应用。     

结合外场观测分析珠三角二次有机气溶胶的数值模拟

结合2008年11月18~25日期间珠三角地区的二次有机气溶胶(SOA)外场观测数据,验证区域空气质量模式WRF/Chem(weather research and forecasting model with chemistry)中两种SOA化学机制——VBS(volatile basis set)和SORGAM(secondary organic aerosol model)对珠三角SOA的模拟效果.VBS机制考虑了更为广泛的SOA前体物和化学老化过程,SOA模拟值更接近观测值,能合理反映SOA观测值的逐天变化趋势,与观测值的平均绝对偏差和相关性分别是-4.88μg·m-3和0.91,而SORGAM机制的分别为-5.32μg·m-3和0.18.利用VBS机制模拟区域内SOA的时空分布,结果显示SOA浓度具有显著的昼夜变化特征,浓度峰值出现在中午时段.受到输送和臭氧区域分布的影响,各城市SOA浓度差异显著,下风向的城市(如中山、珠海、江门)SOA浓度较高.     

生物法脱氮新技术及研究进展

生物法脱氮技术一直是水处理领域所关注的热点和难点。本文对几种近年来新研究的生物法脱氮工艺和理论基础做了简要介绍和分析,并评述了它们的研究进展和发展方向,为污水生物脱氮技术更深入的研究提供了借鉴。