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作 者:吴家辉 WU Jia-hui(Guangzhou Municipal Engineering Design Research Institute Co.,Ltd.,Guangzhou 510000,China)
机构地区:[1]广州市市政工程设计研究总院有限公司,广州510000
出 处:《价值工程》2024年第27期33-35,共3页Value Engineering
摘 要:本文针对城区供水管网改造工程埋管施工的造价预测方法展开研究。采用了一种新颖的混合数据驱动建模技术EPR,该技术基于遗传编程策略,旨在明确识别影响管道的关键因素。研究将管道特征属性纳入建模,通过数学模型与实际数据相结合,清晰地揭示了管道时间、直径、长度等因素对管网改造工程成本的影响。在数据预处理和模型选择阶段,针对数据质量和管道属性,采取了有效的预处理和分类方法。通过多目标优化算法,提出了同时考虑成本和风险的管道替换方案,为决策者提供了科学依据。最终,通过对比单目标方法和多目标方法的结果,证明了多目标方法的优越性和实用性。In this paper,the cost prediction method of buried pipe construction in urban water supply network renovation project is studied.A novel hybrid data-driven modeling technique,EPR,based on genetic programming strategies,was adopted to clearly identify the key factors influencing the pipeline.By combining the mathematical model with the actual data,the paper clearly reveals the influence of pipeline time,diameter,length and other factors on the cost of pipe network renovation project.In the stage of data preprocessing and model selection,effective preprocessing and classification methods are adopted for data quality and pipeline attributes.Through multi-objective optimization algorithm,a pipeline replacement scheme considering both cost and risk is proposed,which provides a scientific basis for decision makers.Finally,by comparing the results of the single objective method and the multi-objective method,the superiority and practicability of the multi-objective method are proved.
分 类 号:TU723.3[建筑科学—建筑技术科学]
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