2024
DOI: 10.3390/app14051748
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Application of a Variable Weight Time Function Combined Model in Surface Subsidence Prediction in Goaf Area: A Case Study in China

Huabin Chai,
Hui Xu,
Jibiao Hu
et al.

Abstract: To attain precise forecasts of surface displacements and deformations in goaf areas (a void or cavity that remains underground after the extraction of mineral resources) following coal extraction, this study based on the limitations of individual time function models, conducted a thorough analysis of how the parameters of the model impact subsidence curves. Parameter estimation was conducted using the trust-region reflective algorithm (TRF), and the time function models were identified. Then we utilized a comb… Show more

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“…RMSE is a unit quantity that clearly shows how much the predicted value deviates from the true value, and MAPE is a percentage quantity without unit dimension, which can visually show the degree of deviation from the predicted value. A higher determination coefficient signifies better performance of the prediction model [32]. R 2 can reflect the degree of regression of data in neural network prediction models.…”
Section: Evaluation Indicators Of Predictive Performancementioning
confidence: 99%
“…RMSE is a unit quantity that clearly shows how much the predicted value deviates from the true value, and MAPE is a percentage quantity without unit dimension, which can visually show the degree of deviation from the predicted value. A higher determination coefficient signifies better performance of the prediction model [32]. R 2 can reflect the degree of regression of data in neural network prediction models.…”
Section: Evaluation Indicators Of Predictive Performancementioning
confidence: 99%