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- W3196863722 abstract "In order to solve the problem that it is difficult to monitor the frequency shift value of the undistributed optical fiber monitoring points in the coal mining distributed optical fiber monitoring, the paper is based on the physical simulation experiment of the distributed optical fiber two-dimensional simulation mining overburden deformation, using the excavation distance and optical fiber monitoring Point height, elastic modulus, tensile strength, compressive strength and other experimental data construct the characteristic attributes of model samples, and propose a distributed optical fiber monitoring frequency shift value prediction algorithm based on GRU-BP. This method is used to predict the frequency shift of unknown monitoring points. It has high accuracy in terms of value, which provides an idea for predicting the frequency shift value at the monitoring point of the unburied fiber. At the same time, the traditional neural network model is established on the premise that the training sample and the test sample are unchanged, and the prediction results of the GRU-BP combined model are compared and analyzed. The experimental results show that: using the GRU-BP algorithm, the prediction effects of R2, MAE, and RMSE can reach 0.91, 0.45, and 0.73, respectively, and their effects are better than traditional neural network models." @default.
- W3196863722 created "2021-09-13" @default.
- W3196863722 creator A5006952581 @default.
- W3196863722 creator A5043301109 @default.
- W3196863722 date "2021-03-01" @default.
- W3196863722 modified "2023-09-23" @default.
- W3196863722 title "Prediction of distributed optical fiber monitoring data based on GRU-BP" @default.
- W3196863722 cites W2599447323 @default.
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- W3196863722 doi "https://doi.org/10.1109/icitbs53129.2021.00063" @default.
- W3196863722 hasPublicationYear "2021" @default.
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