危化品道路运输事故应急救援中心选址模型研究

为快速提高危化品道路运输事故应急救援能力,降低事故后果,文章基于目前应急救援中心选址模型的不足,提出了一种新的双目标决策救援中心选址模型。通过综合考虑应急响应时间及应急处理能力对救援能力的影响,建立了救援中心点的最大网络覆盖模型;并采用较优的邻域搜索算法求解救援中心点的合理位置。最后以某地危化品运输路网为例,利用所建模型对事故应急救援中心的合理布局计算求解。结果表明:考虑应急响应时间及应急处理能力限制的应急救援中心选址模型,能够有效提高救援中心的综合应急能力,为有关部门合理规划危化品道路运输事故应急救援中心布局提供理论参考和决策依据。     

Decision‐making behaviour during urban search and rescue: a case study of Germany

The objective of assisting with tasks and decisions during incident response is to reduce the risks to victims and rescue personnel while increasing the efficiency of the rescue operation. Handling uncertain information during urban search and rescue (USAR) missions represents additional stress to the decision‐maker. The aim of this study is to identify the decision‐making behaviour of rescuers during USAR missions to pinpoint trapped or buried victims in debris in order to design assistance technologies and decision‐support systems that meet their needs. In 2010, a survey was conducted among 10–15 per cent of all German rescue personnel specialised in search tasks. One of the major results of this survey is that a subjective assessment of the reliability of information available from heterogeneous sources influences the rescuers’ actions and that there is no methodology for decision‐making involving uncertain information. In addition, the study found that compliance with procedures does not require assistance.     

和声搜索算法参数的均匀设计

和声搜索算法的参数设置主要是依靠经验和试验来确定,造成试验工作量大且难以得到最优的参数组合,影响了算法的应用.文中通过将和声搜索算法参数设置问题描述成均匀设计中多因素、多水平的试验设计,从而能够用较少的试验很快设置算法参数的取值.仿真试验表明,利用均匀设计得到的参数组合可使算法获得较优的寻优性能,说明了该方法的可行性和有效性.     

数字海洋中海量多源异构空间数据集成研究

针对目前海量多源异构空间数据在组织、管理、集成方面的困难以及传统方法在数据转化过程中造成的数据损耗等问题,结合海洋空间数据的特征,提出一种新的海量多源异构空间数据无缝集成技术(SIMMHS)。该技术针对底层海洋空间数据的海量性和异构性,利用FLEX和XML技术,以XML为数据转换格式,使用XML Schema建立了公共模型,利用虚拟空间数据搜索引擎作为中介实现平台,实现了对海量多源异构空间数据的无缝集成。结合数字海洋上海示范区建设项目的实际应用,有效集成了海量多源异构的空间数据,以方便用户的快速浏览查询、系统的三维展示和数据的实时更新。     

时间压力视角下人格特征与VDT视觉搜索绩效的关系及形成机理*

为合理选拔和培训特定情境下的视觉搜索安检人员,从时间压力视角分析大五人格特征与视觉显示终端（visual display terminal,VDT）的视觉搜索绩效的关系。通过变量分析和设计,提出VDT视觉搜索绩效影响因素理论模型;运用Visual Studio设计实验模拟视觉搜索安检任务,采集绩效及眼动数据;最后进行有中介的调节模型检验。研究结果表明:不同人格特征的VDT视觉搜索绩效存在差异;所有人格特征的搜索策略随机指数随时间压力的增加而降低,但调整强度在不同人格特征之间存在差异,严谨性人格调整幅度最大;时间压力通过搜索策略的中介作用（部分）间接调节人格特征与VDT视觉搜索绩效的关系;较高和较低时间压力下,严谨性人格通过有效的搜索策略调整,绩效最好;中等时间压力下,开放性人格的绩效最好。研究结果可为视觉搜索作业人员的选拔和培训提供理论依据。     

Cracking the humanitarian logistic coordination challenge: lessons from the urban search and rescue community

The challenges of achieving successful inter‐agency logistic coordination in preparing for and responding to natural disasters and complex emergencies are both well understood and well documented. However, although many of these challenges remain unresolved, the literature reveals that the organisations that form the urban search and rescue (USAR) community have attained a high level of coherence and interoperability that results in a highly efficient and effective response. Therefore, this paper uses the idea of ‘borrowing’ from other fields as it explores how the processes and procedures used by the USAR community might be applied to improve humanitarian logistic operations. The paper analyses the USAR model and explores how the resultant challenges might be addressed in a humanitarian logistic context. The paper recommends that further research be undertaken in order to develop a modified USAR model that could be operationalised by the international community of humanitarian logisticians.     

寻求湿度系数与风速关系的数学表达式

在中央气象局编制的《湿度查算表》和GB6999-86《环境试验用相对湿度查算表》的基础上,用最小二乘法与搜索法寻求湿度系数A与风速V关系的数学表达式,提出了湿度系数A适用风速V的参照表,这对提高相对湿度的测量准确度有一定帮助。     

Evaluation of Dynamically Dimensioned Search Algorithm for Optimizing SWAT by Altering Sampling Distributions and Searching Range

The primary advantage of Dynamically Dimensioned Search (DDS) algorithm is that it outperforms other optimization techniques in both convergence speed and searching ability for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation factor) in the optimization process. Conventionally, a default value of 0.2 is used as the perturbation factor, where a normal distribution is applied with mean sampling distribution of zero and variance of one. However, the perturbation factor sensitivity to the performance of DDS for watershed modeling is still unknown. The fixed‐form sampling distribution may result in finding parameters at the local scale rather than global in the sampling space. In this study, the efficiency of DDS was evaluated by altering the perturbation factor (from 0.05 to 1.00) and the selection of sampling distribution (normal and uniform) on hydrologic and water quality predictions in a lowland agricultural watershed in Texas, United States. Results show that the use of altered perturbation factor may cause variations in convergence speed or the ability to find better solutions. In addition, DDS results were found to be very sensitive to sampling distribution selections, where DDS‐N (normal distribution) outperformed DDS‐U (uniform distribution) in all case scenarios. The choice of sampling distributions could be the potential major factor to be attributed for the performance of auto‐calibration techniques for watershed simulation models.     

Application of Tabu Search Algorithm With a Coupled AnnAGNPS‐CCHE1D Model to Optimize Agricultural Land Use1

Abstract: A principal contributor to soil erosion and nonpoint source pollution, agricultural activities have a major influence on the environmental quality of a watershed. Impact of agricultural activities on the quality of water resources can be minimized by implementing suitable agriculture land‐use types. Currently, land uses are designed (location, type, and operational schedule) based on field study results, and do not involve a science‐based approach to ensure their efficiency under particular regional, climatic, geological, and economical conditions. At present, there is a real need for new methodologies that can optimize the selection, design, and operation of agricultural land uses at the watershed scale by taking into account environmental, technical, and economical considerations, based on realistic simulations of watershed response. In this respect, the present study proposes a new approach, which integrates computational modeling of watershed processes, fluvial processes in the drainage network, and modern heuristic optimization techniques to design cost effective land‐use plans. The watershed model AnnAGNPS and the channel network model CCHE1D are linked together to simulate the sediment and pollutant transport processes. Based on the computational results, a multi‐objective function is set up to minimize soil losses, nutrient yields, and total associated costs, while the production profits from agriculture are maximized. The selected iterative optimization algorithm uses adaptive Tabu Search heuristic to flip (switching from one alternative to another) land‐change variables. USDA’s Goodwin Creek experimental watershed, located in Northern Mississippi, is used to demonstrate the capabilities of the proposed approach. The results show that the optimized land‐use design with BMPs using an integrated approach at the watershed level can provide efficient and cost‐effective conservation of the environmental quality by taking into account both productivity and profitability.     

基于随机搜索优化XGBoost的瓦斯涌出量预测模型*

为防治瓦斯灾害,解决井下瓦斯涌出量在预测过程中因影响因素繁多带来的精度较低问题,提出1种基于套索(Lasso)回归与随机搜索优化极限梯度提升(XGBoost)的模型进行瓦斯涌出量预测。以沈阳某煤矿综采面瓦斯涌出量历史数据为例,综合考虑影响瓦斯涌出量的影响因素。首先利用Lasso回归提取对瓦斯涌出量有重要影响的特征数据,作为预测输入;采用随机搜索算法对XGBoost模型4种主要参数进行寻优,选取最优参建立预测模型获得预测指标并分析比较其他模型。研究结果表明:Lasso回归筛选出的影响因素结合随机搜索获得的最优参数组合优化XGBoost比其他模型预测精度更高,平均相对误差为1.53%,均方根误差为0.140 3 m3/min,希尔不等系数为0.013 2,研究结果可为现场瓦斯管理提供参考依据。