贝叶斯规整化BPNN定量流域非点源污染负荷研究

将贝叶斯规整化BP神经网络(BRBPNN)应用于渭河流域非点源污染、社会和经济之间相互作用的研究。采用相关系数法确定输入变量为"降雨"、"种植地"、"草地"、"人口密度"和"羊密度",输出变量为总氮负荷。结果表明用BRBPNN定量非点源污染负荷是可行的,综合选择最优网络模型结构为BRBPNN(3c-7-1),其训练集和预测集相关系数分别为1.0000和0.9780,对应的均方误差分别为88.32和3.21×102。采用权值理论分析各输入因子对网络的贡献,依次为"降雨">"羊密度">"种植地"。该研究可为流域非点源污染的治理提供依据。     

Investigating the impacts of crash prediction models on quantifying safety effectiveness of Adaptive Signal Control Systems

Introduction: Adaptive Signal Control System (ASCS) can improve both operational and safety benefits at signalized corridors. Methods: This paper develops a series of models accounting for model forms and possible predictors and implements these models in Empirical Bayes (EB) and Fully Bayesian (FB) frameworks for ASCS safety evaluation studies. Different models are validated in terms of the ability to reduce the potential bias and variance of prediction and improve the safety effectiveness estimation accuracy using real-world crash data from non-ASCS sites. This paper then develops the safety effectiveness of ASCS at six different corridors with a total of 65 signalized intersections with the same type of ASCS, in South Carolina. Results: Validation results show that the FB model that accounts for traffic volume, roadway geometric features, year factor, and spatial effects shows the best performance among all models. The study findings reveal that ASCS reduces crash frequencies in the total crash, fatal and injury crash, and angle crash for most of the intersections. The safety effectiveness of ASCS varies with different intersection features (i.e., AADT at major streets, number of legs at an intersection, the number of through lanes on major streets, the number of access points on minor streets, and the speed limit at major streets). Conclusions: ASCS is associated with crash reductions, and its safety effects vary with different intersection features. Practical Applications: The findings of this research encourage more ASCS deployments and provide insights into selecting ASCS deployment sites for reducing crashes considering the variation of the safety effectiveness of ASCS.     

基于APRIORI-TAN的交通事故伤害分析与预测*

为探究道路交通事故因素和事故伤害的相关性,以2 467起涉及人员伤亡的交通事故为数据集,运用Apriori算法分别挖掘事故伤害关联规则,并结合社会网络分析的可视化和核心-边缘分析构建受伤事故和死亡事故的关联规则网络。结果表明:事故伤害程度与事故时间、道路条件和交通环境等因素关系紧密,尤其死亡事故与碰撞固定物、人行横道事故、高速公路、高速道路、非市区、酒驾和超速存在高相关性。基于树型贝叶斯网络（TAN）构建事故伤害程度的预测模型,预测结果准确率可达87.56%。     

基于UHBs的输气管道高后果区泄漏燃爆事故分析

为探究输气管道高后果区中人的不安全行为（Unsafe Human Behaviors,UHBs）对输气管道泄漏燃爆事故发生的影响,结合模糊Bow-tie模型和贝叶斯网络对输气管道泄漏燃爆事故进行分析。构建基于T-S模糊故障树的输气管道泄漏燃爆模糊Bow-tie模型,并转化为贝叶斯网络;从人的不安全行为发生的可能性出发,将不同等级高后果区划分为不同等级人口敏感区;利用专家经验评判法得到不同等级人口敏感区基本事件的先验概率和中间事件的条件概率表;运用贝叶斯网络双向推理算法求解模糊Bow-tie模型。结果表明:随着地区人口敏感等级的提高,输气管道泄漏燃爆事故发生的概率随之增大,发现导致输气管道失效泄漏事故发生的最主要原因为施工破坏,失效原因与EGIG分析的结果基本相符,验证该方法在高后果区输气管道泄漏燃爆事故分析上的可行性,可为输气管道高后果区的安全管理提供决策依据。     

化石能源地生态承载力研究

针对当前研究中忽略化石能源地生态承载力的不足,从土地碳吸收功能的角度将生态足迹法与净初级生产力相结合,根据构建的化石能源地生态承载力模型,对东北地区进行了实证研究.结果表明,2004-2008年,东北地区化石能源地生态承载力的区域性差异显著,辽宁最低、吉林居中、黑龙江最高;三省人均化石能源地生态承载力均呈缓慢下降趋势,...     

Research on the prediction model of hazardous chemical road transportation accidents

In recent years, hazardous chemicals road transport accidents have occurred frequently, causing huge casualties and property losses, and accident risk assessment has become the focus of researchers' research. To predict the risk probability value of hazardous chemical road transport accidents, first, we compiled data on road transportation accidents of hazardous chemicals in China in the past five years. And the nine nodes in the Bayesian network (BN) structure were defined in combination with relevant classification standards. The optimal Bayesian network structure for hazardous chemical road transport accidents was determined based on the K2 algorithm and the causalities between the nodes. Second, the node conditional probabilities were derived by parameter learning of the model using Netica, and the validity of the model was verified using the 5-fold cross-validation method. Last, the Bayesian network model of hazardous chemical road transport accidents is used to analyze accident examples, and the accident chain of “rear-end-leakage” is predicted, and the accident is most likely to be disposed of within 3–9 h. The study shows that the derived accident prediction model for hazardous chemical road transportation can reason reasonably about the evolution of accident scenarios and determine the probability values of accident risks under different parameter conditions.     

基于置信规则的村镇应急避难场所暴雨灾害链风险诊断*

为解决村镇应急避难场所面临暴雨灾害时的风险问题,基于故障树和置信规则库推理方法,提出暴雨灾害链和村镇应急避难场所功能破坏链相结合的场所避难功能失效风险诊断模型。根据事故致因理论推理灾害节点变量,通过故障树描述灾害链,运用关联规则从历史灾害数据中挖掘规则,建立置信规则库系统,构建村镇应急避难场所功能失效风险诊断模型,并以四川省某寄宿制学校为例进行模型验证。研究结果表明:该模型可实现不同证据组合下村镇应急避难场所功能失效风险的诊断推理;实例的模型诊断结果与实际情况吻合,证实该模型能够科学地诊断村镇应急避难场所面临暴雨等恶劣自然条件时存在的风险,可为村镇应急避难场所规划设计和应急管理提供理论支撑。     

储罐腐蚀及清罐周期合理性研究

描述了腐蚀对储罐的影响,并使用贝叶斯判别预测方法对储罐腐蚀状况进行了预测,合理确定了储罐清罐周期。     

基于毕达哥拉斯模糊贝叶斯网络的海底管道泄漏风险分析*

为分析海底管道运行中存在的泄漏风险,提出1种基于毕达哥拉斯模糊数与贝叶斯网络的风险评估模型。首先,通过毕达哥拉斯模糊数转换专家定性评价,拓展专家意见模糊范围;然后,结合主客观组合赋权法,利用毕达哥拉斯梯形爱因斯坦混合几何算子（PTFEHG）实现专家意见的聚合;最后,通过贝叶斯网络的推理与敏感性分析,计算海底管道泄漏风险的失效概率,并辨识关键风险因素。研究结果表明:该方法可以结合专家意见对海底管道泄漏风险进行定量分析,并识别导致泄漏事故的关键风险因素,对海底管道安全管理具有指导意义。     

基于模糊Petri网的有载分接开关故障诊断方法研究*

为解决分接开关故障诊断以主观经验、缺乏系统化流程以及诊断结果与分接开关实际发生故障存在偏差等问题,依据当前分接开关主要故障分类,提出基于模糊Petri网的有载分接开关故障诊断模型,并结合分接开关典型故障案例,验证模型有效性。研究结果表明:基于模糊Petri网的分接开关故障诊断模型能够有效处理故障概率中不确定性因素,具有容错性好、运行效率高等优势,研究结果可为提高分接开关故障诊断的准确性、保障电力系统安全稳定运行提供参考。