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Discussion on the prediction of engineering cost based on improved BP neural network algorithm

机译:基于改进BP神经网络算法的工程成本预测探讨

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摘要

With the continuous improvement of the social and economic level, the investment in fixed assets in the whole society is increasing steadily, while the phenomenon of uncontrollable investment is becoming more and more serious. Therefore, it is very important to increase the investment estimate in the early stage of the project construction. Based on this, in this paper, by studying the BP neural network, a mathematical model of the prediction of engineering cost based on the improved BP neural network model was proposed; then, taking a 15-storey tall building in a residential district as a prediction object, by collecting and sorting out engineering cost data similar to the predicted object, the improved BP neural network model was estimated and trained; finally, the prediction of the engineering cost data for the project was carried out, and the actual results were compared with the estimation results of the traditional prediction model; thus, the speediness and accuracy of the proposed improved BP neural network model in the field of the prediction of engineering cost were verified.
机译:随着社会和经济水平的不断提高,整个社会中固定资产的投资正在稳步增长,而无法控制的投资现象变得越来越严重。因此,在项目建设的早期阶段增加投资估计是非常重要的。基于这,本文通过研究了BP神经网络,提出了一种基于改进的BP神经网络模型的工程成本预测的数学模型;然后,在住宅区进行一个15层高的高层建筑作为预测对象,通过收集和分类类似于预测对象的工程成本数据,估计和培训了改进的BP神经网络模型;最后,进行了对项目的工程成本数据的预测,并将实际结果与传统预测模型的估计结果进行了比较;因此,验证了在工程成本预测领域中提出的改进的BP神经网络模型的速度和准确性。

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