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电力工程造价是一个多变量、非线性的复杂过程,以往的电力工程项目造价中经常需要分析研究人员通过经验分析和主观推测,对工程造价进行概预算定额测算。如何利用已建工程的历史造价资料,为新建电力工程项目造价管理提供比较合理的判断和比较科学的理论分析,需要运用准确的数据挖掘知识。本文基于“电力工程中许多成本元素互相作用影响,最终体现在工程造价”这样一个特点,将BP神经网络运用在对电力工程造价问题的研究,搭建了工程造价的快速分析模型,通过对实际数据的模拟研究,确定了该模型的可行性和有效性。
The cost of power engineering is a complex process with many variables and nonlinearities. In the past, the cost of power engineering projects often needs to be analyzed and researched by researchers through empirical analysis and subjective speculation. How to use the historical cost information of the constructed projects to provide more reasonable judgment and comparatively scientific theoretical analysis for the cost management of the newly-built power engineering projects requires the knowledge of accurate data mining. Based on the fact that many cost elements in electric power project interact with each other, and ultimately reflected in the cost of construction, this paper applies BP neural network to the research on the cost of power engineering and sets up a rapid analysis model of project cost. The actual data simulation study, to determine the feasibility of the model and effectiveness.