海外铁路建设项目造价人工智能估算方法研究

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摘要 研究目的:海外铁路建设项目投资估算亟需一套集可靠的历史数据和科学的估算方法于一体的估价体系,来解决因投资估算效率与准确度低而导致项目亏损的问题。本文运用PSO(Particle Swarm Optimization)和BPNN(Back Propagation Neural Network)等非线性方法建立海外铁路投资智能估算模型,以弥补传统估算方法主观性强、可靠性低等不足。
研究结论:(1)识别出包括建设市场、地质条件等在内的19个海外铁路投资估算影响因素;(2)研究发现,PSO和BPNN等非线性方法可较好地适用于海外铁路投资估算的研究中;(3)通过实证研究,本文所构建模型误差控制在6.44%以内,准确度较高,可以推广运用于国内地铁、高铁投资估算领域;(4)本文研究可为其他海外铁路建设项目造价的估算研究提供参考。

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	段晓晨
	鲍默
	牛衍亮
	雷培军

关键词 ：海外铁路, PSO, BPNN, 智能估算

Abstract：Research purposes: The investment estimation of overseas railway construction projects urgently needs a valuation system integrating reliable historical data and scientific estimation methods to solve the problem of project losses due to the low efficiency and accuracy of investment estimation. This paper uses nonlinear methods such as PSO (Particle Swarm Optimization) and BPNN (Back Propagation Neural Network) to establish an intelligent estimation model for overseas railway investment to make up for the shortcomings of traditional estimation methods such as strong subjectivity and low reliability.
Research conclusions:(1) 19 factors affecting the overseas railway investment estimation are identified, including construction market and geological conditions. (2) It is found that the nonlinear methods such as PSO and BPNN can be well applied to the study of overseas railway investment estimation. (3) Through empirical research, the error of the model established in this paper is controlled within 6.44%, with high accuracy, which can be popularized and applied to the investment estimation of subway and high-speed railway in China. (4) This research can provide reference for other overseas railway construction project cost estimation research.

Key words： overseas railway BPNN PSO intelligence estimate

收稿日期: 2021-06-30

PACS:

F282

基金资助:国家自然科学基金面上项目(72071133);河北省自然科学基金项目(G2019210226);河北省“巨人计划”第三批创新创业团队(冀办字〔2018〕33号);河北省研究生创新资助项目(CXZZSS2020062);河北省高等学校人文社会科学研究(青年拔尖人才)2019年度项目(BJ2019079);河北省省属高校(石家庄铁道大学)基本科研业务费研究项目(SQK202002)

作者简介: ^**段晓晨,1962年出生,男,教授,博士生导师。

引用本文:

段晓晨, 鲍默, 牛衍亮, 雷培军. 海外铁路建设项目造价人工智能估算方法研究[J]. 铁道工程学报, 2022, 39(9): 112-118.
DUAN Xiaochen, BAO Mo, NIU Yanliang, LEI Peijun. Cost Estimation Method for Overseas Railway Construction Project Based on Artificial Intelligence. Journal of Railway Engineering Society, 2022, 39(9): 112-118.

链接本文:

https://tdgcxb.crec.cn/CN/ 或 https://tdgcxb.crec.cn/CN/Y2022/V39/I9/112

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