An Optimization Method for Estimating Constituent Mean Concentrations in Base Flow‐Dominated Flow

Pollutant coefficients have been widely used to assess runoff nonpoint source pollution from individual land uses (e.g., agricultural, residential) of a watershed. Pollutant coefficients, known as event mean concentrations (EMCs), were developed by the U.S. Environmental Protection Agency's Nationwide Urban Runoff Program (NURP) to serve as a national measure for characterizing pollutant loading in a receiving water body. The term “baseflow pollutant coefficient (BPC)” is used in this study as a surrogate for EMC to describe mean concentration of pollutants in base flow‐dominated flow. A method for characterizing base flow quantity and quality for different land uses was explored using inverse modeling with two optimization techniques (a least square method and a genetic algorithm [GA] optimization), land use information, and streamflow quantity and quality data. The inverse model was formulated as a constrained minimization problem and demonstrated with data for 15 watersheds in Indiana. Results showed that estimated pollutant coefficients are comparable to the published literature. This indicates that the proposed method has the potential to effectively estimate constituent mean concentrations for pollutant load determination in gauged and ungauged watersheds, albeit more analysis with larger and more robust datasets is desirable to further refine and validate the accuracy of the approach.     

微生物处理技术在有机污染物降解中的应用

微生物处理有机污染物是一种费用低,效果好,无二次污染且操作简单的处理方法。综述了国内外几种微生物处理有机污染物技术的研究进展。     

基于SVR的船舶溢油事故预测

船舶溢油事故的预测,是确定所需应急资源多少的重要依据;但船舶溢油事故具有小样本性,传统预测方法不再适用。针对船舶溢油事故的小样本性,该文选择SVR模型对其进行预测;SVR算法的关键是核函数的选择及自由参数的确定,针对上述问题该文分别采用交叉验证法、遗传算法;并在matlab软件上建立SVR模型,最后将该模型应用于上海港水域船舶溢油事故的预测。     

Developing a fuzzy linear programming model for locating recovery facility in a closed loop supply chain

In this research a closed loop supply chain is designed which incorporates reverse logistics and forward logistic system simultaneously. In the design of reverse logistic system, recovery options are embedded in traditional supply chain for treating returned products. The recovery system includes collection centres, remanufacturing plants and disposal centres. Since the product return is supply driven, there is an uncertainty about it. In the proposed configuration for closed loop supply chain, the optimised configuration for supply chain in terms of locating recovery plants is developed. Accordingly, a fuzzy mixed integer linear programming model develops to deal with the uncertainty of returning products by customers. A general-purpose solver (LINGO 8.0) and a Meta heuristic approach (genetics algorithm) are implemented to solve the proposed model. The answers are compared by defining indexes and then the optimal answer, configuration and variables are identified. This solution will suggest a new design of supply chain network in which waste of materials is minimised and the new raw materials are necessary only when the used products may not be recovered by recovery options.     

An analytical platform for cumulative impact assessment based on multiple futures: the impact of petroleum drilling and forest harvesting on moose (Alces alces) and marten (Martes americana) habitats in northeastern British Columbia

The combined influence on the environment of all projects occurring in a single area is evaluated through cumulative impact assessments (CIA), which consider the consequences of multiple projects, each insignificant on its own, yet important when evaluated collectively. Traditionally, future human activities are included in CIA using an analytical platform, commonly based on complex models that supply precise predictions but with reduced accuracy. To compensate for the lack of accuracy in current CIA approaches, we propose a shift in the paradigm governing CIA. The paradigm shift involves a change in the focus of CIA investigations from the detailed analysis of one unlikely future to the identification of the patterns describing multiple potential future changes in the environment. To illustrate the approach, a set of 144 possible and equally likely futures were developed that aimed to identify the potential impacts of forest harvesting and petroleum drilling on the habitat suitability of moose and marten in northeast British Columbia, Canada. The evolution of two measures of habitat suitability (average habitat suitability index and surface of the stands with habitat suitability index >0.5) revealed that the human activities could induce cycles in the habitat dynamics of moose and marten. The planning period of 100 years was separated into three distinct periods following a sinusoidal pattern (i.e., increase - constant - decrease in the habitat suitability measures). The attributes that could induce significant changes in the assessment of environment are the choice of harvesting age and species.     

铁路危险货物办理站点优化配置方法研究

铁路危险货物运输办理站点的优化配置,涉及到需求分布、设置地点、区域规划、环保要求、业务功能以及与其他运输方式的分工、衔接等,是一个复杂的系统工程。分析了已有铁路危险货物办理站点整合优化模型的不足,首先从铁路部门角度综合考虑现有铁路危险货物办理站点的各方面条件,进行多准则决策评价,从运输需求者角度考虑运输方式多属性决策,进行铁路危险货物办理站点的综合效用评价,并基于投资成本、环境风险、运输效用和区域公平性等方面构建了铁路危险货物办理站点优化配置模型,为了有效解决多站点、多需求、多区域、多目标铁路危险货物办理站点优化配置模型因素复杂、规模大、层次多的问题,提出了运用大系统分解协调的多目标遗传算法求解模型的思路。     

基于GA优化算法的平遥县大气环境质量评价研究

本文以平遥县城及周边区域环境空气质量监测结果为依据,采用具有全局优化的遗传算法（GA）对平遥县及周边区域大气环境质量污染现状进行评价。用大气污染危害指数的普适公式和参数优化后的污染危害指数公式确定污染危害指数的取值范围与评价级别之间的对应关系,由此得出较符合平遥县及周边区域实际的评价结果,同时针对具体情况对此结果进行简单的分析。     

长柄石杉居群遗传多样性和遗传结构的AFLP分析

石杉科植物因所含石杉碱甲(Huperzine A)对中老年痴呆等具有良好疗效,近年来倍受关注.利用AFLP分子标记对武夷山脉广布种长柄石杉[Huperzia serrata(Thunb.ex Murray)Trev.var.longipetiolata(Spring)H.M.Chang]7个居群112株个体进行遗传多样性和居群遗传结构分析.选用多态性高、分辨力强的8对选择性扩增引物组合共获得675个位点,其中多态位点比例为69.38%.居群内观测等位基因数(Na)为1.633,有效等位基因数(Ne)1.493;Nei’s基因多样性指数(He)与Shannon多态性信息指数(I)的平均值分别为0.272和0.392,多样性最高为地处武夷山脉中段的泰宁居群和建宁居群,最低为山脉北段的光泽居群.居群总基因多样性(Ht)为0.327 3,居群内基因多样性(Hs)为0.272 2,居群间的遗传分化系数(Gst)为0.168 1,表明居群内变异是长柄石杉遗传多样性的主要来源.由Gst估计,武夷山脉长柄石杉自然居群的基因流(Nm)为2.474 0.邻接树分析表明居群间遗传亲缘关系与地理位置相关.武夷山脉长柄石杉较高的遗传多样性和基因流水平表明其仍然具有相当的适应(生存)能力和进化潜力,这可能与其生物学(异交水平)、生态学特性及武夷山脉相对良好的生境条件有关.     

基于遗传算法的支持向量机预测有机物自燃点的研究

根据定量构效关系(QSPR)原理,研究自燃点(AIT)与其分子结构间的内在定量关系。以265种有机化合物作为样本集,随机选择238种作为训练集,27种作为测试集,用遗传算法(GA)进行变量选择,分别建立多元线性回归(MLR)模型和支持向量机(SVM)模型研究有机物的自燃点与其分子结构间的关系。通过分析,发现造成模型预测效果不佳的原因是试验数据本身存在问题。通过对2个模型的比较,结果为GA-SVM模型明显优于GA-MLR模型,说明自燃点与其分子结构间具有很强的非线性关系。     

基于在线检测信息的储罐底板腐蚀状态智能评价方法

为了解决利用声发射在线检测技术对储罐底板腐蚀状态进行评价时,主要依赖检测人员经验的问题,使该项技术能更好地推广和应用,利用储罐底板在线检测的声发射信息和外观检查信息,并根据相关标准及专家经验,确定与储罐底板腐蚀状态相关的表征因素。采用遗传算法(GA)改进贝叶斯网络(BN)搜索方法,建立基于GA的BN智能评价方法。针对声发射在线检测信息和外观检查信息,分别建立基于标准用声发射因素、基于声发射因素和综合考虑声发射因素和外观检查因素的基于在线检测信息的储罐底板腐蚀状态评价模型。通过对测试样本的评价,对比声发射检测专家评价结果,其中基于在线检测信息的储罐底板腐蚀状态评价模型的准确率为96%,该模型能够对储罐底板腐蚀状态进行可靠的智能评价。