This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal c...This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.展开更多
This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing app...This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.展开更多
针对国省干线人因交通事故的异质性特点,提出一种事故链式因果推断方法,实现交通事故因果机制辨识与交互效应量化的同步解析。首先,采集新疆11条国省干线近年交通事故信息构建数据集,利用K-prototype聚类算法将事故严重程度分为3类;其次...针对国省干线人因交通事故的异质性特点,提出一种事故链式因果推断方法,实现交通事故因果机制辨识与交互效应量化的同步解析。首先,采集新疆11条国省干线近年交通事故信息构建数据集,利用K-prototype聚类算法将事故严重程度分为3类;其次,基于结构因果模型、因果森林及SHAP(SHapley Additive exPlanation)算法构建链式因果推断模型,推理出事故关键致因链、多维诱因交互效应及事故类别概率预测值,解析“场景组合-人为要素-事故类别”的链式传导特征及异质性特点;最后,基于SHAP值分析多维要素贡献度,并结合因果效应强度划分行为致因类别,辨识出事故关键人为致因,提出具有针对性的事故防控策略。结果表明:本文所提方法的加权平均F1得分与宏平均AUC(Area Under Curve)值分别为0.86与0.82,相对高于常用的机器学习算法,且克服了传统关联模型难以实现多因素交互作用机制刻画与效应量化的局限,适宜人因事故异质机理解构分析;由致因链分析可知,人为要素为事故主要致因,天气和时段等环境要素对事故后果均有显著影响,恶劣环境与危险行为的综合作用对事故程度升级具有非线性影响作用;超速行驶、疲劳驾驶、跟车过近与观察不周为核心行为致因,营运类车辆出现上述行为后事故严重程度相对较高,严重型事故占比超过50%,应重点进行事故监测与防控。展开更多
为揭示养老机构安全事故的致因机制,基于2015—2024年89起司法案例、事故报告和理赔案例,构建融合故障树分析(Fault Tree Analysis,FTA)与贝叶斯网络(Bayesian Network,BN)的致因链模型,系统识别并量化关键风险因素及其复杂交互关系。...为揭示养老机构安全事故的致因机制,基于2015—2024年89起司法案例、事故报告和理赔案例,构建融合故障树分析(Fault Tree Analysis,FTA)与贝叶斯网络(Bayesian Network,BN)的致因链模型,系统识别并量化关键风险因素及其复杂交互关系。结果表明,养老机构安全事故致因链呈现出多路径耦合与节点聚集的结构特征;少数高敏感性因素如安全意识淡薄、护理人员培训不足在不同事故类型中反复出现,成为事故链条中的关键驱动要素;不同事故类型在致因链上既呈现出独特的演化路径,又在关键致因节点上存在显著共性特征。展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.90209010)NBRP2003CB715900.
文摘This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.
文摘This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.
文摘针对国省干线人因交通事故的异质性特点,提出一种事故链式因果推断方法,实现交通事故因果机制辨识与交互效应量化的同步解析。首先,采集新疆11条国省干线近年交通事故信息构建数据集,利用K-prototype聚类算法将事故严重程度分为3类;其次,基于结构因果模型、因果森林及SHAP(SHapley Additive exPlanation)算法构建链式因果推断模型,推理出事故关键致因链、多维诱因交互效应及事故类别概率预测值,解析“场景组合-人为要素-事故类别”的链式传导特征及异质性特点;最后,基于SHAP值分析多维要素贡献度,并结合因果效应强度划分行为致因类别,辨识出事故关键人为致因,提出具有针对性的事故防控策略。结果表明:本文所提方法的加权平均F1得分与宏平均AUC(Area Under Curve)值分别为0.86与0.82,相对高于常用的机器学习算法,且克服了传统关联模型难以实现多因素交互作用机制刻画与效应量化的局限,适宜人因事故异质机理解构分析;由致因链分析可知,人为要素为事故主要致因,天气和时段等环境要素对事故后果均有显著影响,恶劣环境与危险行为的综合作用对事故程度升级具有非线性影响作用;超速行驶、疲劳驾驶、跟车过近与观察不周为核心行为致因,营运类车辆出现上述行为后事故严重程度相对较高,严重型事故占比超过50%,应重点进行事故监测与防控。
文摘为揭示养老机构安全事故的致因机制,基于2015—2024年89起司法案例、事故报告和理赔案例,构建融合故障树分析(Fault Tree Analysis,FTA)与贝叶斯网络(Bayesian Network,BN)的致因链模型,系统识别并量化关键风险因素及其复杂交互关系。结果表明,养老机构安全事故致因链呈现出多路径耦合与节点聚集的结构特征;少数高敏感性因素如安全意识淡薄、护理人员培训不足在不同事故类型中反复出现,成为事故链条中的关键驱动要素;不同事故类型在致因链上既呈现出独特的演化路径,又在关键致因节点上存在显著共性特征。
