Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context

Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.     

长江三角洲城市旅游与城市发展协调性及影响因素

城市旅游业作为城市服务业的重要部门,是推动城市发展的后续动力。运用信息熵赋权法和TOPSIS法相结合,从经济水平、社会发展、公共交通、城市绿化、环境保护、旅游发展6个方面对长江三角洲2003年和2008年的城市旅游与城市发展的协调性进行分析,借助ArcGIS软件的空间聚类法分析了城市旅游与城市发展协调水平的空间格局及演变,最后探讨影响因素。结果表明:长江三角洲16城市的城市旅游协调水平在研究期间相对稳定,具体可被划分为4个等级,第一、二等级城市数量较少,得分显著高于第三、四等级城市。城市旅游协调水平空间上存在较大差异,北部城市得分高于南部城市,基本格局保持稳定,呈现以上海、南京、杭州三个城市为核心向外围边缘城市的空间衰减。产业发展、城市旅游发展模式、城市旅游重大项目投资、区位条件是长江三角洲城市旅游协调水平产生空间分化的主要影响因素,可制定以城市旅游发展为手段的方式推动城市发展,促进区域均衡发展。     

基于改进TOPSIS法的规划环评情景方案建立方法及应用

目前,情景分析法在规划环评中进行应用时,情景方案的建立方法仍存在较大不确定性。针对这一问题,结合广西石化产业规划环评,为在广西区6个重点城市分布44个石化项目建立多套可行方案,以供后续方案筛选。通过层次分析法计算出影响因素特性的权重,将改进后的多属性决策TOPSIS方法引入规划环评,并与情景分析法相结合。探讨了基于TOPSIS法对构建情景方案的影响因素进行筛选,并最终确定核心因子的新方法。结论为：利用筛选出的三种核心因子——规划相容性、资源环境因子和产业链结构——构建出了18套情景方案,作为规划环评的初始可行方案,并在三维坐标系中分别将这些方案表示出来,从而实现了将方案定量化、形象化,为规划环评中后续方案筛选提供了定量化科学依据。     

基于熵权TOPSIS模型的土地利用多功能性诊断

从经济、社会和生态3个方面出发构建土地利用多功能性评价指标体系，应用熵权TOPSIS模型对江苏省近年来土地利用多功能性进行诊断分析可以优化区域土地的合理开发，提高土地利用效率，为促进区域的可持续发展提供有效依据。研究结果表明：2006~2016年江苏省土地利用综合功能经历了一般—良好的发展阶段，综合功能在不断优化；经济功能经历了较差—一般—良好—优秀—良好的发展阶段，虽然有所波动,但其依旧呈增长态势；社会功能经历了较差—一般—良好—优秀的发展阶段，呈现出持续稳步提高趋势；生态功能经历了一般—良好—一般的发展趋势，整体呈下降趋势。另外土地利用的经济功能和社会功能子目标的障碍度在逐年下降，对目前江苏省土地利用有效性起制约作用的主要是生态功能，应减少废水排放和工业固体废弃物等污染造成的生态破坏，加强水资源的保护，同时缩小城乡差距，推进城乡融合，促进土地利用过程中经济、社会和生态功能的协调发展。     

中国省际农业碳排放测算及低碳化水平评价——基于衍生指标与TOPSIS法的运用

农业碳排放量测算及低碳化水平评价,是实现农业绿色发展和制定碳减排计划的重要依据。通过测算2006—2016年中国30个省份的农业碳排放量,并以测算结果为基础,从农业用地、禽畜养殖和农业能源三个方面构造农业碳排放衍生指标,采用基于动态自然权重的TOPSIS法对各省农业低碳化水平进行评价。结果表明：中国农业碳排放总量呈先降后升的“V型”变化,由2006年的91096万t下降至2008年的83521万t,此后稳步增加至2016年的92192万t。农业非能源碳排放量占农业碳排放总量的84%以上,土壤管理是农业非能源碳排放的第一来源。省际农业碳排放衍生指标异质性较强,农业低碳化水平整体不高。研究结果可为农业和环境部门开展低碳农业评价工作提供借鉴。     

TOPSIS法在大气环境质量评价中的应用

应用多目标决策中的TOPSIS法(即逼近于理想解的排序方法)对湖南长沙等十城市的大气环境质量进行评价,并与欧几里德贴近度法和上海指数法相比较,认为该评价方法对比较多个城市(或多个监测点,下同)的大气环境质量的优劣,比欧几里德贴近度法和上海指数法均优越.     

能源富集区市域经济发展水平空间格局演变——基于晋陕蒙甘宁地区

采用熵权TOPSIS法对我国晋陕蒙甘宁这一典型能源富集区各地级以上城市的市域经济发展水平进行综合评价,进而使用马尔可夫转移概率分析方法和ESDA空间分析方法,探索该地区市域经济发展水平时空分异格局的演化特征,结果显示：（1）该地区的市域经济发展差距在波动中下降;（2）各等级城市在不同时期演化规律截然相反,随时间推移,除低等级之外的各等级城市均表现出较高的等级下降风险;（3）该地区城市的市域经济水平曾存在一定空间负相关,到2015年这种关系则不再显著;（4）该地区呈现以局部为核心区的格局,但西部地区明显趋冷;（5）市域经济系统整体处于耦合协调度较低的状态,发展不平衡、不协调的问题较突出。     

基于改进TOPSIS的受灾点需求紧迫性分级研究

地震发生初期,各受灾点对物资需求的紧迫性存在差异。在应急资源有限的情况下,为提高救援效率,应急资源需要按照受灾点需求紧迫性优先级进行分配和调度。首先,构建了受灾点需求紧迫性评价指标体系,并采用博弈论方法将熵权法和层次分析法相结合,确定权重组合系数及各评价指标综合权重。其次,利用马氏距离和灰色关联分析改进TOPSIS方法,建立了受灾点应急物资需求紧迫性分级模型。最后,将模型应用于受灾点应急物资需求紧迫性分级研究,并将该评价结果与传统TOPSIS法的评价结果进行比较,结果表明,该评价方法可以科学、客观地确定权重组合系数,消除指标间相关性,使评价结果符合实际情况,表明该评价方法科学、可行、有效,能为应急救援物资配送提供有效支持和决策。     

基于GPR-TOPSIS方法的充填配比多目标多属性优化

为获得某金矿尾砂胶结充填材料最优配比,基于试验结果,以海水比例、灰砂比和料浆质量浓度为输入参数,以充填体强度、塌落度及泌水率为输出参数,建立了充填配比与其响应量的高斯过程回归模型,分析了不同因素对充填性能的影响程度;采用遗传算法对高斯过程回归模型进行多目标参数优化,获得了Pareto非劣解,在此基础上,引入多属性决策的TOPSIS法对Pareto非劣解进行方案优选,确定了充填最优配比。研究结果表明:高斯过程回归模型相对误差值均小于6%,可靠性高;灰砂比及料浆质量浓度对充填性能影响较为显著,采用海水作为充填水源将降低充填体的强度;经优化后的充填配比与试验结果相符。