文章摘要
王雁.基于BIM的地震灾后民用建筑重建工程施工成本控制方法[J].地震工程学报,2019,41(1):233-238. WANG Yan.BIM-based Method for the Cost Control of CivilBuilding Reconstruction after Earthquakes[J].China Earthquake Engineering Journal,2019,41(1):233-238.
基于BIM的地震灾后民用建筑重建工程施工成本控制方法
BIM-based Method for the Cost Control of CivilBuilding Reconstruction after Earthquakes
投稿时间:2018-10-01  
DOI:10.3969/j.issn.1000-0844.2019.01.233
中文关键词: 成本控制;灰度系统预测;BIM;粗糙集理论;施工重建
英文关键词: cost control;gray system prediction;BIM;rough set theory;reconstruction
基金项目:国家自然科学基金资助项目(41672261)
作者单位
王雁 湖南省核工业建设有限公司, 湖南 长沙 410000
南华大学经济管理学院, 湖南 衡阳 421001 
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中文摘要:
      采用传统的成本控制方法,存在质量和成本无法同时优化、成本预测精确度低,成本控制效果不佳等问题,为此,提出基于BIM的建筑重建工程施工成本控制方法。采用灰色系统理论预测建筑施工成本具体面临的问题,以各期施工成本相关信息数据作为模型数据基础;结合BIM技术进行成本控制动态模型构建,在模型中引入可辨识矩阵设定成本各指标的相对重要度,进一步找寻施工成本各项指标间的关系,按其相互关系进行排序,得到子成本与总成本间的规则联系,并就规则制定控制策略,调整成本控制动态模型以实现施工成本的动态控制。实验结果表明,所提方法的成本预测精度始终在75%以上,成本控制结果与实际值的拟合度高达95%,相比当前方法具有更好的控制性能。
英文摘要:
      The traditional cost control method exhibits several problems, i.e., nonsimultaneous quality and cost optimization, low cost prediction accuracy, and poor cost control effect. Therefore, a method based on BIM for the cost control of reconstruction projects is proposed in this work. The gray system theory is used to forecast the concrete problems associated with construction cost, and the construction cost-related information data of each period is used as the model data base. The dynamic model of cost control is constructed in combination with BIM technology. Then, the relative importance of each cost index is set by introducing a discernibility matrix. The relationship between the different indexes of construction cost is further investigated, and the rules underlying the connection between subcost and total cost are obtained. The control strategy is developed in accordance with the identified rules, and the cost control dynamic model is adjusted to dynamically control construction cost. Experimental results show that the cost prediction accuracy of the proposed method consistently exceeds 75% and that the fitting degree between the cost control result and the actual value reaches 95%. The proposed method has better control performance than the currently applied method.
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