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Application of computer technology in construction cost management

机译:计算机技术在建筑工程造价管理中的应用

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This research uses Matlab to write neural network programs and processes extraction samples, processing samples and predictive value of output automated and intelligent in construction project cost management. It focuses on the grey RBF neural network applied in estimating construction project cost, and use the actual construction work and civil engineering to validate and evaluate the program. By analyzing error, it is concluded that the estimate should take samples from the amount of cost value approximately equal in construction cost. In other words, the higher value project should take the same number as lower value project. It is good to use computer software for construction cost management, It’s easier to extract samples of buildings, extract and eliminate features, normalize and denormalize samples, input sample and output prediction. Then we can get the prediction of construction cost value. This makes building engineering cost management more automated. It makes actual managers can focus on actual projects rather than the specific details of the operation.
机译:本研究使用Matlab编写神经网络程序,并在工程项目成本管理中自动,智能地处理提取样本,处理样本以及输出的预测值。它着重于灰色RBF神经网络在估算建筑项目成本中的应用,并利用实际的建筑工程和土木工程来验证和评估该程序。通过分析误差,可以得出以下结论:估算应从与建筑成本大致相等的成本值中抽取样本。换句话说,高价值项目应采用与低价值项目相同的编号。最好使用计算机软件来管理建筑成本,更容易提取建筑物样本,提取和消除特征,对样本进行归一化和非归一化,输入样本和输出预测。然后我们可以得到建筑成本价值的预测。这使建筑工程成本管理更加自动化。它使实际管理者可以将重点放在实际项目上,而不是操作的特定细节上。

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