探究投资管理视角下炼化工程造价历史数据的盘活  

Investigating the Activation of Historical Cost Data in Petrochemical Engineering from an Investment Management Viewpoint

作　　者：王震 WANG Zhen(Engineering Quota Management Station of Sinopec Group,Qingdao 266000,China)

机构地区：[1]中国石油化工集团有限公司工程定额管理站,青岛266000

出　　处：《铁路工程技术与经济》2025年第2期22-28,共7页Railway Engineering Technology and Economy

摘　　要：在第四次工业革命的推动下,人工智能作为新一代数字信息技术的先锋迅速崛起,为工程造价领域带来了前所未有的机遇与挑战。作为一种重要的数据资产,工程造价历史数据在炼化工程投资建设中具有极高的利用价值。然而,这些工程造价历史数据常常未被充分挖掘利用。文章首先探讨了炼化行业投资管理的现状。进而,深入分析了现阶段历史工程造价数据的应用现状及其存在的问题。确定了历史工程造价数据在项目决策、投资估算、预算以及竣工结算中的核心作用。随后,文章详细阐述了历史工程造价数据的收集、处理和分析方法,特别是如何通过最小二乘支持向量机与粒子群算法技术深度挖掘其价值。最后,针对盘活历史工程造价数据所面临的挑战,提出相关建议。通过深度挖掘历史工程造价数据的价值,不仅可以提升投资管理的效率和精确度,还能推动项目实现绿色、健康及可持续发展。Driven by the Fourth Industrial Revolution,artificial intelligence,as a vanguard of the new generation of digital information technology,has rapidly emerged,bringing unprecedented opportunities and challenges to the field of engineering cost.As a vital data asset,historical engineering cost data holds significant utility in the investment and construction of petrochemical projects.However,these data are often not fully exploited.This paper first discusses the current state of investment management in the petrochemical industry.It then delves into an analysis of the current application status and existing problems of historical engineering cost data.The core role of historical engineering cost data in project decision-making,investment estimation,budgeting,and final settlement is identified.Subsequently,the paper elaborates on the methods of collecting,processing,and analyzing historical engineering cost data,with a focus on how to deeply mine its value through least squares support vector machines and particle swarm optimization techniques.Finally,in response to the challenges faced in revitalizing historical engineering cost data,relevant suggestions are proposed.By deeply mining the value of historical engineering cost data,not only can the efficiency and precision of investment management be enhanced,but it can also promote the green,healthy,and sustainable development of projects.

关 键 词：炼化工程 投资管理 工程造价 历史数据盘活 人工智能技术 

分 类 号：F426[经济管理—产业经济]