城市可持续发展评价的分指数及综合指数公式

在指标按特征分类的基础上，提出了城市可持续发展评价分类指标的分指数公式和多类别组合的综合指数公式。应用遗传算法对公式中的参数进行优化，得到简单而适用的城市可持续发展评价模型。模型应用于全国“七五”，“八五”可持续发展评价结果与实际分析结果一致。该模型具有可比性强，通用性好和简单，实用的特点。     

The Boundary-Quality Penalty: a Quantitative Method for Approximating Species Responses to Fragmentation in Reserve Selection

Abstract:  Aggregation of reserve networks is generally considered desirable for biological and economic reasons: aggregation reduces negative edge effects and facilitates metapopulation dynamics, which plausibly leads to improved persistence of species. Economically, aggregated networks are less expensive to manage than fragmented ones. Therefore, many reserve-design methods use qualitative heuristics, such as distance-based criteria or boundary-length penalties to induce reserve aggregation. We devised a quantitative method that introduces aggregation into reserve networks. We call the method the boundary-quality penalty (BQP) because the biological value of a land unit (grid cell) is penalized when the unit occurs close enough to the edge of a reserve such that a fragmentation or edge effect would reduce population densities in the reserved cell. The BQP can be estimated for any habitat model that includes neighborhood (connectivity) effects, and it can be introduced into reserve selection software in a standardized manner. We used the BQP in a reserve-design case study of the Hunter Valley of southeastern Australia. The BQP resulted in a more highly aggregated reserve network structure. The degree of aggregation required was specified by observed (albeit modeled) biological responses to fragmentation. Estimating the effects of fragmentation on individual species and incorporating estimated effects in the objective function of reserve-selection algorithms is a coherent and defensible way to select aggregated reserves. We implemented the BQP in the context of the Zonation method, but it could as well be implemented into any other spatially explicit reserve-planning framework .     

应用水色卫星遥感技术估算珠江口海域溶解有机碳浓度

溶解有机碳是水域环境评价的必测环境参数之一。根据水体光学理论，利用在珠江口水域实测的水体成分浓度数据集拟水体光谱，并建立溶解有机碳浓度的遥感反演模式。进而应用新一代海洋水色卫星传感器SeaWiFS资料估算珠江口及其邻近水域溶解有机碳浓度。     

基于模糊层次分析法的警用非致命空气炮作战效能评估

目的评估警用非致命空气炮的作战效能。方法首先运用层次分析法,确立警用非致命空气炮作战效能评估指标体系,构建作战效能的模糊层次综合评判模型,并采用加权平均算法和平均随机一致性指标,进行各因素权重计算和一致性检验,最后通过模糊综合评判,评估得出警用非致命空气炮作战效能。结果警用非致命空气炮综合评估得分为82.92分,其性能评估为"较好"。结论通过评估结果,反映出警用非致命空气炮综合作战效能较好,具有推广价值和应用前景,为空气炮优化设计和实战应用提供了参照。     

人工神经网络和遗传算法在生物载体填料生产工艺中的应用

本文应用BP人工神经网络建立了生物流化床污水处理工艺中新型生物载体填料的生产工艺参数与填料磨损破碎率和松散容重之间的关系，并运用遗传算法对填料的生产工艺进行了优化。结果表明：填料的最佳生产工艺参数为：EVA含量14％；活性炭含量3．6％；胶粉粒度18.97目。此时，填料的磨损破碎率和松散容量均达到最优值，分别为0．358％和0．226kg／L。这一优化结果对生物载体填料的实际生产加工具有指导意义。     

BOD-DO耦合人工神经网络水质模拟的研究

将人工神经网络的理论和方法引入河流水质模型的建筑中，提出了BOD－DO耦合BP人工神经网络水质模型，应用长江干流重庆段的实测水质样本对模型进行训练与 检验表明：该模型用于水质模拟可行且精度较高，为河流水质模拟开辟了一条简便可行的新途径。     

Analyzing the factors affecting environmental risks of projects using a hybrid approach of DEMATEL‐ANP,artificial neural network: A case study

The increasing growth of the economy in each country necessitates a great amount of investment in infrastructure. The belief that projects involve various uncertainties, such as technical skills, management quality, and the like, indicates that most projects fail to achieve their aims, interests, costs, as well as their timeframes and space requirements. As the environment can pose significant uncertainty to any project, environmental risks should be deeply studied by project management departments. This study intends to analyze as a case the environmental risk management system within a consulting firm. From this analysis, each aspect of a project's environmental risk management is ranked using a fuzzy analytical network process (ANP), a neural network algorithm, and a decision‐making trial and evaluation laboratory (DEMATEL) methodology. From the organizational aspect, budget risk is the most significant. From the technical aspect, the risk of regulations is the most important one. Finally, the risk of project failure from poor communication is another identified main risk in this research. By studying high‐ranking items in this hierarchy, it can be understood that these criteria exist in different aspects; therefore, all aspects of the risk should be taken into account to cover and assess risk. A neural network algorithm for validating and reassessment of ranking is employed. Results of this application showed that, based on Spearman's rank correlation method, two different approaches resulted in similar rankings. Finally, some practical implications for responding to the most highly ranked risks are proposed.     

基于LCS的应急决策文本相似性比对分析模型

作为应急管理中的主要工作内容,应急决策在整个应急管理工作中具有战略意义,为了对危机情境下的应急决策主体进行聚类分析,定量计算不同决策主体之间相应决策文本的区别。借鉴最长公共子序列模型（LCS）的原理,从决策文本中提取主题词,根据决策文本的特点将其分为“目标”和“行动”2级,结合样本总体确定替换矩阵、空位罚分规则和目标函数,构建高层应急决策文本相似性比对分析模型;运用Needleman Wunsch算法对该模型进行求解;通过对得到的地震情景下的高层应急决策文本的分析,证明模型的有效性和可行性;为了避免序列长度差过大对聚类分析的结果影响,在此基础上提出相对相似性得分的概念,并通过与VSM算法得到的结果进行比较,证明该模型在应急决策文本相似性分析中的优越性。     

基于SVM的通风系统故障诊断惩罚系数与核函数系数优化研究

使用支持向量机（SVM）方法对矿井通风系统进行故障诊断,存在惩罚系数（c）和核函数系数（g）,通过人工方法选取效率低、难以达到较高准确率并且出现过拟合的问题。为了提高矿井通风故障诊断的效率、准确率,同时避免过拟合现象,提出了一种改进遗传算法（GA）,在故障诊断过程中对支持向量机的c,g参数进行优化。经过多组试验分析,研究结果表明:用遗传算法优化的SVM矿井通风故障诊断系统相比于未优化系统的故障诊断准确率有所提升,参数未优化前故障诊断的准确率为60%,优化后的准确率为97.894 7%,并且优化参数经过大数据样本验证,未出现过拟合现象,证明了本文提出方法的有效性。     

基于受体易损性分析的环境风险综合评价方法研究

针对我国现有环境风险评价体系中缺乏对自然环境、人工环境损失进行量化评价这一问题,在以往研究的基础上,建立了符合我国特点的受体易损性区划指标体系与量化模型,结合事故影响预测,建立了风险值计算方法,并提出了基于Bootstrap算法的环境风险可接受水平确定方法,由此构建了一套新的环境风险综合评价方法体系。