Prediction of Construction Schedule Based on BP Neural Network

2013 ◽  
Vol 405-408 ◽  
pp. 3423-3428
Author(s):  
Zhao Lin Li ◽  
Guo Zhi Zhang
Keyword(s):  
Neural Network ◽  
Project Management ◽  
Bp Neural Network ◽  
Linear Method ◽  
Schedule Control ◽  
Construction Schedule

Schedule control is the major issue in project management, and to predict the construction schedule effectively is important practically. The article mainly predicts the schedule of a project based on BP neural network. The result shows that the predicted value is more accurate than the value calculated by linear method.

Economic benefit of shale gas exploitation based on back propagation neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang
Keyword(s):  
Neural Network ◽  
Shale Gas ◽  
Bp Neural Network ◽  
Large Scale ◽  
Linear Prediction ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Economic Benefits ◽  
Gas Well ◽  
Well Production

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods

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