Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm
Abstract Water damage accidents occur frequently in mines in China, and accurate prediction of incoming water has become an important guarantee for the safe and efficient mining of coal resources. To improve the accuracy of mine water prediction, this paper proposes the VMD-iCHOA-GRU mine water pred...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-82580-8 |
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| author | Juntao Chen Mingjin Fan |
| author_facet | Juntao Chen Mingjin Fan |
| author_sort | Juntao Chen |
| collection | DOAJ |
| description | Abstract Water damage accidents occur frequently in mines in China, and accurate prediction of incoming water has become an important guarantee for the safe and efficient mining of coal resources. To improve the accuracy of mine water prediction, this paper proposes the VMD-iCHOA-GRU mine water prediction model by selecting and improving it according to the previous research results in decomposition method, time series prediction model and optimization algorithm. After processing the raw data and setting the model parameters, MAE, RMSE, MAPE and R2 are selected as the evaluation indexes of prediction accuracy, and VMD-GRU model, iCHOA-GRU model, CHOA-GRU model and GRU model are selected as the comparison models to validate the advantages of the VMD-iCHOA-GRU model in the prediction of mine inrush water. The results show that the VMD-iCHOA-GRU model has the best prediction effect on the trend of water inflow, with the evaluation index values of 0.00862, 0.01059, 0.02189%, 0.87079, respectively, and with the smallest MAE, RMSE, MAPE, and the largest R2, and the highest prediction accuracy of the VMD-iCHOA-GRU model. |
| format | Article |
| id | doaj-art-0928cab228f846d3b67bb8253bb73c86 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-0928cab228f846d3b67bb8253bb73c862025-02-09T12:29:18ZengNature PortfolioScientific Reports2045-23222025-02-0115111810.1038/s41598-024-82580-8Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithmJuntao Chen0Mingjin Fan1College of Energy and Mining Engineering, Shandong University of Science and TechnologyCollege of Energy and Mining Engineering, Shandong University of Science and TechnologyAbstract Water damage accidents occur frequently in mines in China, and accurate prediction of incoming water has become an important guarantee for the safe and efficient mining of coal resources. To improve the accuracy of mine water prediction, this paper proposes the VMD-iCHOA-GRU mine water prediction model by selecting and improving it according to the previous research results in decomposition method, time series prediction model and optimization algorithm. After processing the raw data and setting the model parameters, MAE, RMSE, MAPE and R2 are selected as the evaluation indexes of prediction accuracy, and VMD-GRU model, iCHOA-GRU model, CHOA-GRU model and GRU model are selected as the comparison models to validate the advantages of the VMD-iCHOA-GRU model in the prediction of mine inrush water. The results show that the VMD-iCHOA-GRU model has the best prediction effect on the trend of water inflow, with the evaluation index values of 0.00862, 0.01059, 0.02189%, 0.87079, respectively, and with the smallest MAE, RMSE, MAPE, and the largest R2, and the highest prediction accuracy of the VMD-iCHOA-GRU model.https://doi.org/10.1038/s41598-024-82580-8Water damage accidentsVariational mode decompositionImproved chimp optimization algorithmGated recurrent units |
| spellingShingle | Juntao Chen Mingjin Fan Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm Scientific Reports Water damage accidents Variational mode decomposition Improved chimp optimization algorithm Gated recurrent units |
| title | Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm |
| title_full | Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm |
| title_fullStr | Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm |
| title_full_unstemmed | Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm |
| title_short | Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm |
| title_sort | mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm |
| topic | Water damage accidents Variational mode decomposition Improved chimp optimization algorithm Gated recurrent units |
| url | https://doi.org/10.1038/s41598-024-82580-8 |
| work_keys_str_mv | AT juntaochen minewaterinflowpredictionmodelbasedonvariationalmodedecompositionandgatedrecurrentunitsoptimizedbyimprovedchimpoptimizationalgorithm AT mingjinfan minewaterinflowpredictionmodelbasedonvariationalmodedecompositionandgatedrecurrentunitsoptimizedbyimprovedchimpoptimizationalgorithm |