Risk Assessment and Prediction of Construction Project Based on 1D-CNN-Attention-BP ()
ABSTRACT
In order to solve the problem of low accuracy of construction project duration prediction, this paper proposes a CNN attention BP combination model project risk prediction model based on attention mechanism, one-dimensional convolutional neural network (1d-cnn) and BP neural network. Firstly, the literature analysis method is used to select the risk evaluation index value of construction project, and the attention mechanism is used to determine the weight of risk factors on construction period prediction; then, BP neural network is used to predict the project duration, and accuracy, cross entropy loss function and F1 score are selected to comprehensively evaluate the performance of 1d-cnn-attention-bp combined model. The experimental results show that the duration risk prediction accuracy of the risk prediction model proposed in this paper is more than 90%, which can meet the risk prediction of construction projects with high accuracy.
Share and Cite:
Zhong, Y. (2021) Risk Assessment and Prediction of Construction Project Based on 1D-CNN-Attention-BP.
World Journal of Engineering and Technology,
9, 861-876. doi:
10.4236/wjet.2021.94059.
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