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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Research on Mathematical Model of Cost Budget in the Early Stage of Assembly Construction Project Based on Improved Neural Network Algorithm
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Research on Mathematical Model of Cost Budget in the Early Stage of Assembly Construction Project Based on Improved Neural Network Algorithm

机译:基于改进神经网络算法的大会建设项目早期成本预算数学模型研究

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摘要

In view of the poor performance of the original mathematical model of assembly construction project precost budget, a mathematical model of assembly construction project precost budget based on improved neural network algorithm is proposed. This paper investigates the cost content of assembly construction project and analyzes its early cost. It finds that the early cost of assembly construction project includes component production cost, transportation component cost, and installation component cost. Based on the improved neural network algorithm to build an improved neural network model, the improved neural network model to mine the cost data in the early stage of assembly construction project is used. In this paper, the earned value variable is introduced to transform the project duration and project cost in the early stage of the prefabricated construction project into quantifiable cost data, and the earned value analysis method is used to estimate the implementation cost of the prefabricated construction project. According to the result of cost estimation, the mathematical model of precost budget of prefabricated construction project is built based on the project parameters. In order to prove that the cost budget performance of the mathematical model based on the improved neural network algorithm in the early stage of assembly construction project is better, the original mathematical model is compared with the mathematical model, the experimental results show that the cost budget performance of the model is better than the original model, and the cost budget performance is improved.
机译:鉴于组装建设项目预算的原始数学模型的性能不佳,提出了一种基于改进神经网络算法的组装建设项目预级预算的数学模型。本文调查了装配建设项目的成本含量,并分析了其早期成本。它认为,装配建筑项目的早期成本包括元件生产成本,运输成本成本和安装部件成本。基于改进的神经网络算法构建改进的神经网络模型,使用了改进的神经网络模型来挖掘装配施工项目的早期阶段的成本数据。在本文中,引入了赚取的价值变量,以将预制建筑项目的早期阶段转换为可量化的成本数据,并且赚取的值分析方法用于估计预制建设项目的实施成本。根据成本估算的结果,基于项目参数构建了预制建设项目预预算的数学模型。为了证明基于组装建设项目的早期提高神经网络算法的数学模型的成本预算性能更好,原始数学模型与数学模型进行比较,实验结果表明成本预算该模型的性能优于原始模型,成本预算表现得到改善。

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