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基于主成分分析法的灌区工程施工风险研究 被引量:3

Study on Construction Risk of Irrigation Canal Based on Principal Component Analysis
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摘要 以河南省赵口引黄灌区二期工程为例,建立基于主成分分析法的灌区工程施工风险研究模型。运用矩阵线性变换原理构建主成分分析数学模型,通过矩阵运算提取部分可观测综合指标。构造函数计算风险类别及各施工工序的综合得分,得分越高风险越大。结果可知,得分最高的工序是水闸闸门施工,其次是倒虹吸混凝土浇筑;得分高的主要风险因素为设计方案合理性,其次是施工组织设计方案合理性。针对工序和施工风险的重要性,给出了风险防控对策。 Taking the second-phase project of Zhaokou Yellow River Irrigation District in Henan Province as an example,the construction risk research model of irrigation district is established based on principal component analysis.The mathematical model of principal component analysis is constructed by using the principle of matrix linear transformation,and some observable comprehensive indexes are extracted by matrix operation.The evaluation function is constructed to calculate the risk category and the comprehensive score of each construction procedure,and the higher the score is,the higher the risk is.The analysis results show that the process with highest score is sluice gate construction,followed by inverted siphon concrete pouring,and the main risk factor with highest score is the rationality of design scheme,followed by the rationality of construction organization design scheme.According to the importance of construction process and risk,the risk prevention and control measures are proposed.
作者 杨子照 魏淑卿 张继勋 张辉 李涵曼 YANG Zizhao;WEI Shuqing;ZHANG Jixun;ZHANG Hui;LI Hanman(College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210024,Jiangsu,China;Construction Administration of The Second Phase Project of Zhaokou Irrigation District of The Yellow River in Henan Province,Kaifeng 475000,Henan,China;State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Nanjing Hydraulic Research Institute,Nanjing 210029,Jiangsu,China)
出处 《水力发电》 CAS 2023年第4期63-68,86,共7页 Water Power
基金 国家自然科学基金黄河水科学研究联合基金(U2243-223) 中央级公益性科研院所基本科研业务费专项资金项目(Y722003)。
关键词 大型灌区 施工期 风险源 主成分分析 矩阵线性变换 防控对策 large-scale irrigation area construction period risk source principal component analysis matrix linear transformation countermeasures
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