| 政府监督数据驱动的工程建设质量风险全景式预警模型 |
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| 引用本文： | 张 可,周雨欣,张 政,马 敏.政府监督数据驱动的工程建设质量风险全景式预警模型[J].工程管理学报,2022,36(6):144-149. |
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| 作者姓名： | 张 可 周雨欣 张 政 马 敏 |
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| 作者单位： | 1,2,3,4. 河海大学 商学院;1,2,3,4. 河海大学 项目管理研究所 |
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| 摘 要： | 工程建设质量关乎国民经济可持续发展与人民群众生命财产安全，准确预警质量风险是有效预防质量事故的重要基础。政府监督在质量管理体系中具有重要地位，分析政府监督数据的多元时间序列特征及质量风险特征提取的全局性和全过程性要求，引入共同主成分分析提取区域项目集群的全局质量风险特征，采用门控循环单元挖掘工程建设全过程的关键风险特征，基于两种特征构建工程建设质量风险全景式预警模型，以满足政府监督的风险管控需求。将模型应用于实例，结果表明:其能够有效识别监管重点并准确预警工程质量风险。
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| 关 键 词： | 政府监督 工程质量风险 多元时间序列 共同主成分分析 门控循环单元 |
A Panoramic Early Warning Model of Construction Quality Risk Drivenby Government Supervision Data |
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| ZHANG Ke,,ZHOU Yu-xin,,ZHANG Zheng,,MA Min,.A Panoramic Early Warning Model of Construction Quality Risk Drivenby Government Supervision Data[J].Journal of Engineering Management,2022,36(6):144-149. |
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| Authors: | ZHANG Ke ZHOU Yu-xin ZHANG Zheng MA Min |
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| Affiliation: | 1,2,3,4. School of Business， Hohai University;1,2,3,4. Institute of Project Management， Hohai University |
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| Abstract: | The project construction quality has a certain impact on the national economy’s sustainable development and the safetyof people’s lives and property. Accurate early warning of quality risks is an important basis for effective quality accident prevention.Government supervision plays an essential role in the quality management system. The multivariate time series characteristic ofgovernment supervision data and the overall and whole-process requirements for the risk characteristics extraction are first analyzed.Then， the common principal component analysis is introduced to extract the regional project cluster’s global quality riskcharacteristics. The key historical characteristics of the whole project construction process are excavated by the gated cycle unit.Finally， based on the above two characteristics， a panoramic risk early warning model of engineering construction quality isconstructed to meet government supervision’s risk control needs. The model’s application result shows that this model can effectivelyidentify the key points of supervision and accurately warn of project quality risks. |
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| Keywords: | government supervision project quality risk multivariate time series common principle component analysis gatedrecurrent unit |
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