Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

种族鱼群优化支持向量机序列理论监测尾矿坝

为监测预警尾矿坝的变形位移,提出基于结构风险最小化理论的支持向量机进行学习预测。通过采集有效数据,对时间序列数据进行归一化序列处理,然后采取种族鱼群选择向量机参数,对处理后的数据进行支持向量机回归预测。将该理论应用到某尾矿坝监测系统,得到了较为准确的预测结果,表明该理论充分利用了数据的统计特性,精度和泛化能力都得到了明显提高,可作为尾矿坝监测系统的有效指导。     

A Water Allocation Decision‐Support Model and Tool for Predictions in Ungauged Basins in Northeast British Columbia,Canada

Pressures on water resources due to changing climate, increasing demands, and enhanced recognition of environmental flow needs result in the need for hydrology information to support informed water allocation decisions. However, the absence of hydrometric measurements and limited access to hydrology information in many areas impairs water allocation decision‐making. This paper describes a water balance‐based modeling approach and an innovative web‐based decision‐support hydrology tool developed to address this need. Using high‐resolution climate, vegetation, and watershed data, a simple gridded water balance model, adjusted to account for locational variability, was developed and calibrated against gauged watersheds, to model mean annual runoff. Mean monthly runoff was modeled empirically, using multivariate regression. The modeled annual runoff results are within 20% of the observed mean annual discharge for 78% of the calibration watersheds, with a mean absolute error of 16%. Modeled monthly runoff corresponds well to observed monthly runoff, with a median Nash–Sutcliffe statistic of 0.92 and a median Spearman rank correlation statistic of 0.98. Monthly and annual flow estimates produced from the model are incorporated into a map‐ and watershed‐based decision‐support system referred to as the Northeast Water Tool, to provide critical information to decision makers and others on natural water supply, existing allocations, and the needs of the environment.     

大气污染总量控制规划智能决策支持系统的开发与研究

对大气污染总量控制规划智能决策支持系统的开发步骤和总体结构做了介绍。并描述了该系统中的知识库系统、模型库系统、数据库系统和图形库系统的设计思想,特别是对知识库的构造进行了较详细的叙述。还介绍了神经网络技术在该系统中的应用。指出大气污染总量控制规划智能决策支持系统将为大气污染总量控制提供更科学、更合理、更有效的规划方案。     

中国省级环境决策支持系统的系统分析

中国省级环境决策支持系统(DSS)是基于GIS和各种模型的空间决策支持系统?该文介绍了DSS系统的系统分析方法和内容,包括软件需求说明?数据需求说明和总体设计      

复杂河流系统水污染的计算机图形模拟

讨论在河流系统水污染规划中应用交互式计算机图形技术。通过对复杂河流系统水污染的图形模拟,提出建立图模型的一般理论和方法,并就浑太流域河流水污染案例给出实际模拟结果。     

高效液相色谱法测定茶叶和土壤中的氟

建立了测定氟的高效液相色谱法,并通过加入三乙胺使Ｆ－Ｌａ＾３＋－苯素氨羧络合剂体系更稳定。Ｃ１８柱,甲醇－水（１８：８２）作流动相,流速为１ｍｌ／ｍｉｎ,检测波长为５６６ｎｍ,本法线性范围为０．０１０－１．０μｇ／ｍｌ,相关系数为０．９９１,检出限为１ｎｇ／ｍｌ,用于茶叶和土壤样品测定时,相对标准偏差为４．６％－７．３％,加标回收率为９１％￣１０４％。     

SELECTION AND SUSTAINABILITY OF LAND AND WATER RESOURCE MANAGEMENT SYSTEMS1

ABSTRACT: Most spatial decision support systems for natural resource planning and management are limited by their scenario-based (non-behavioral), deterministic (non-stochastic) structure. A spatial decision support system is developed that uses a multiple attribute decision-making model to explain how a property manager selects a land and water resource management system (LWRMS) based on its multiple, stochastic economic and environmental attributes. The decision support system assesses sustainable resource management at the property and watershed scales and identifies the most cost-effective policy for enhancing sustainable resource management. Economic attributes are determined with an economic model and environmental attributes are simulated with an environmental model. Input parameters for both models are generated with a geographic information system. The decision support system is used to rank five LWRMS for a sample of 20 farmers in Missouri's Goodwater Creek watershed and for two hypothetical watershed alliance groups. Results indicate that the average farmer and the two alliance groups would rank the five LWRMS in the same manner. From the viewpoint of the watershed alliance, the most preferred LWRMS for the average farmer in the watershed is sustainable.     

Effective conservation planning of Iberian amphibians based on a regionalization of climate-driven range shifts

Amphibians are severely affected by climate change, particularly in regions where droughts prevail and water availability is scarce. The extirpation of amphibians triggers cascading effects that disrupt the trophic structure of food webs and ecosystems. Dedicated assessments of the spatial adaptive potential of amphibian species under climate change are, therefore, essential to provide guidelines for their effective conservation. I used predictions about the location of suitable climates for 27 amphibian species in the Iberian Peninsula from a baseline period to 2080 to typify shifting species’ ranges. The time at which these range types are expected to be functionally important for the adaptation of a species was used to identify full or partial refugia; areas most likely to be the home of populations moving into new climatically suitable grounds; areas most likely to receive populations after climate adaptive dispersal; and climatically unsuitable areas near suitable areas. I implemented an area prioritization protocol for each species to obtain a cohesive set of areas that would provide maximum adaptability and where management interventions should be prioritized. A connectivity assessment pinpointed where facilitative strategies would be most effective. Each of the 27 species had distinct spatial requirements but, common to all species, a bottleneck effect was predicted by 2050 because source areas for subsequent dispersal were small in extent. Three species emerged as difficult to maintain up to 2080. The Iberian northwest was predicted to capture adaptive range for most species. My study offers analytical guidelines for managers and decision makers to undertake systematic assessments on where and when to intervene to maximize the persistence of amphibian species and the functionality of the ecosystems that depend on them.     

湖北省应急物资保障体系探析

为深入贯彻落实习近平总书记关于健全统一的应急物资保障体系,把应急物资保障作为国家应急管理体系建设重要内容的重要讲话精神,总结分析湖北省应急物资保障体系现状,针对湖北省自然灾害和事故灾难救援救灾任务的情况,分析目前湖北省应急物资保障体系存在的问题及对策措施,为"十四五"提升应急物资保障能力提供参考.