【摘 要】
：
The major factors influencing subsidence factor were comprehensively analyzed. Then the artificial neural network model for calculating subsidence factor was set up with the theory of artificial neural network (ANN). A large amount of data from observatio
【机 构】
：
School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China
论文部分内容阅读
The major factors influencing subsidence factor were comprehensively analyzed. Then the artificial neural network model for calculating subsidence factor was set up with the theory of artificial neural network (ANN). A large amount of data from observation stations in China was collected and used as learning and training samples to train and test the artificial neural network model. The calculated results of the ANN model and the observed values were compared and analyzed in this paper. The results demonstrate that many factors can be considered in this model and the result is more precise and closer to observed values to calculate the subsidence factor by the ANN model. It can satisfy the need of engineering.
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