支持向量机在边坡稳定性预测中的应用

针对离子型稀土原地浸矿边坡稳定性问题的小样本、非线性等特点,采用一种边坡稳定性预测模型——支持向量机(SVM)模型,分别使用网格参数寻优、遗传算法(GA)参数寻优、粒子群(PSO)寻优算法来计算SVM模型的参数,分析比较3种算法得到的参数,确定最适合离子型稀土原地浸矿边坡稳定性预测的SVM回归模型的参数寻优算法。     

基于集对论和主客观综合赋权法的装备保障能力评估研究

目的提出一种基于集对论和主客观赋权法的装备保障能力评估方法。方法针对装备保障能力评估中存在的诸多不确定问题,构建装备保障能力评估指标体系,基于集对论思想建立装备保障能力集对评估模型。结果通过构造一个双目标决策问题,进行主客观综合赋权确定指标权重,使得评估指标权重向量同时反映了主观程度和客观程度。结论该方法通过联系度量化了评估指标的确定程度,提高了评估结果的可信性,对解决装备保障能力评估中不确定性问题具有很强的指导作用。     

基于PCA-AHPSO-SVR的煤层瓦斯含量预测研究

为了提高煤层瓦斯含量预测的准确性和科学性,通过主成分分析方法对影响煤层瓦斯含量的7个因素进行特征提取,消除影响因素之间的相关性,减少维度;用支持向量回归机对提取的因素进行训练,并用改进的自适应混合粒子群算法对SVR的参数进行优化,提出PCA-AHPSO-SVR模型;与PCA-PSO-SVR,PSO-SVR这2个模型在相同环境下进行30次运行比较。研究结果表明:研究提出的PCA-AHPSO-SVR模型较其他2种模型平均准确率分别提高5.51%和9.32%,稳定性更佳,可满足工程实际需求。     

高应力大变形软岩巷道“三壳”围岩控制机理及应用

为解决土城煤矿14运输上山软岩巷道变形量大、锚杆索失效严重等技术难题,通过现场调研、室内试验、理论分析、数值模拟及工业性试验等方法,揭示了围岩变形特征以及巷道失稳破坏机理,提出了“三壳”围岩控制理论。基于以上研究,设计了“锚杆锚索+灌浆+钢管混凝土支架”的复合支护方案,建立了基于“三壳”围岩控制理论的“三壳”支护结构体力学模型,计算出设计方案的极限承载能力为2.54 MPa,随后采用 FLAC3D数值模拟软件对设计方案进行模拟分析,验证了方案合理性。最后,该复合支护得到成功运用,现场监测结果表明:巷道顶底板以及两帮变形量均低于100 mm,巷道未发生明显变形,支护效果良好。     

基于属性约简的绝缘节破损预测

准确的绝缘节破损预测能够保证铁路运输安全和经济效益。支持向量机算法能够处理轨道电路测试数据,对其进行分类,预测可能存在隐患的绝缘节,但支持向量机预测模型的原始样本多有冗余,基于此,提出了一种基于粗糙集和支持向量机的绝缘节破损预测模型。通过改进主分量启发式属性约简算法,降低样本维数,同时选用模拟退火算法完成SVM自动参数选优。实例分析和仿真结果表明,与单一支持向量机算法相比,属性约简后的粗糙集-支持向量机算法提高了分类器的分类性能,与采用网格搜索技术的SVM预测方法相比,模拟退火算法有效提高了SVM的预测精度。     

支持向量机对多环芳烃毒性的定量构效预测

为了实现多环芳烃(PAHs)毒性的有效预测,提出应用定量构效技术对多环芳烃的空气-正辛醇分配系数(KOA)和致癌性进行预测。应用分子描述符和试验值确立构效关系,采用支持向量机算法(SVM)和人工神经网络算法(ANN)分别建立了PAHs的KOA回归预测模型和致癌性分类预测模型。利用网格划分(GS)、遗传算法(GA)、粒子群算法(PSO)对SVM进行参数寻优。应用均方误差(MSE)、拟合决定系数R2和分类准确率(Accuracy)分别对模型进行了验证与评价。结果表明,最佳回归预测模型GS-SVR的MSE为0.059 7,R2为0.913 0;最佳分类预测模型GA-SVC的Accuracy为95%。研究表明:应用SVM所建两种模型的稳定性和预测能力都优于应用ANN建立的模型;参数优化后模型的稳定性和预测能力得到了提高。     

The effectiveness of lane departure warning systems—A reduction in real-world passenger car injury crashes

Objective: The objective of this study was to estimate the safety benefits of in vehicle lane departure warning (LDW) and lane keeping aid (LKA) systems in reducing relevant real-world passenger car injury crashes.

Methods: The study used an induced exposure method, where LDW/LKA-sensitive and nonsensitive crashes were compared for Volvo passenger cars equipped with and without LDW/LKA systems. These crashes were matched by car make, model, model year, and technical equipment; that is, low-speed autonomous emergency braking (AEB) called City Safety (CS). The data were extracted from the Swedish Traffic Accident Data Acquisition database (STRADA) and consisted of 1,853 driver injury crashes that involved 146 LDW-equipped cars, 11 LKA-equipped cars, and 1,696 cars without LDW/LKA systems.

Results: The analysis showed a positive effect of the LDW/LKA systems in reducing lane departure crashes. The LDW/LKA systems were estimated to reduce head-on and single-vehicle injury crashes on Swedish roads with speed limits between 70 and 120 km/h and with dry or wet road surfaces (i.e., not covered by ice or snow) by 53% with a lower limit of 11% (95% confidence interval [CI]). This reduction corresponded to a reduction of 30% with a lower limit of 6% (95% CI) for all head-on and single-vehicle driver injury crashes (including all speed limits and all road surface conditions).

Conclusions: LDW/LKA systems were estimated to lower the driver injury risk in crash types that the systems are designed to prevent; that is, head-on and single-vehicle crashes. Though these are important findings, they were based on a small data set. Therefore, further research is desirable to evaluate the effectiveness of LDW/LKA systems under real-world conditions and to differentiate the effectiveness between technical solutions (i.e., LDW and LKA) proposed by different manufacturers.     

Growth of the Decision Tree: Advances in Bottom‐Up Climate Change Risk Management

There has recently been a return in climate change risk management practice to bottom‐up, robustness‐based planning paradigms introduced 40 years ago. The World Bank's decision tree framework (DTF) for “confronting climate uncertainty” is one incarnation of those paradigms. In order to better represent the state of the art in climate change risk assessment and evaluation techniques, this paper proposes: (1) an update to the DTF, replacing its “climate change stress test” with a multidimensional stress test; and (2) the addition of a Bayesian network framework that represents joint probabilistic behavior of uncertain parameters as sensitivity factors to aid in the weighting of scenarios of concern (the combination of conditions under which a water system fails to meet its performance targets). Using the updated DTF, water system planners and project managers would be better able to understand the relative magnitudes of the varied risks they face, and target investments in adaptation measures to best reduce their vulnerabilities to change. Next steps for the DTF include enhancements in: modeling of extreme event risks; coupling of human‐hydrologic systems; integration of surface water and groundwater systems; the generation of tradeoffs between economic, social, and ecological factors; incorporation of water quality considerations; and interactive data visualization.     

A Hydraulic MultiModel Ensemble Framework for Visualizing Flood Inundation Uncertainty

While deterministic forecasts provide a single realization of potential inundation, the inherent uncertainty associated with forecasts also needs to be conveyed for improved decision support. The objective of this study was to develop an ensemble framework for the quantification and visualization of uncertainty associated with flood inundation forecast maps. An 11‐member ensemble streamflow forecast at lead times from 0 to 48 hr was used to force two hydraulic models to produce a multimodel ensemble. The hydraulic models used are (1) the International River Interface Cooperative along with Flow and Sediment Transport with Morphological Evolution of Channels solver and (2) the two‐dimensional Hydrologic Engineering Center‐River Analysis System. Uncertainty was quantified and augmented onto flood inundation maps by calculating statistical spread among the ensemble members. For visualization, a series of probability flood maps conveying the uncertainty in forecasted water extent, water depth, and flow velocity was disseminated through a web‐based decision support tool. The results from this study offer a framework for quantifying and visualizing model uncertainty in forecasted flood inundation maps.     

轨道交通项目环评的指标体系及管理与决策支持系统研究

为解决城市轨道交通项目环评缺乏完整的评价指标体系及评估结果不够可靠、环评报告资料难以管理和利用等问题,参考DPSIR模型提出了包括3个层次的指标体系,并设计了其管理与决策支持系统,对其总体框架、功能体系、实现和部署进行了深入讨论。通过案例分析,提出的指标体系和系统具有较强的实用性,对指导环评工作具有一定意义。