Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction method
Abstract As an important link in the complex system engineering project of open pit mining, the quality of the boundary determines the performance of the project to a large extent. However, changes in economic indicators may raise doubts about the optimality of mining boundaries. In this article, a...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-34641-7 |
| _version_ | 1797827588580704256 |
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| author | Bo Cao Shuai Wang Runcai Bai Bo Zhao Qingyi Li Mingjia Lv Guangwei Liu |
| author_facet | Bo Cao Shuai Wang Runcai Bai Bo Zhao Qingyi Li Mingjia Lv Guangwei Liu |
| author_sort | Bo Cao |
| collection | DOAJ |
| description | Abstract As an important link in the complex system engineering project of open pit mining, the quality of the boundary determines the performance of the project to a large extent. However, changes in economic indicators may raise doubts about the optimality of mining boundaries. In this article, a coal price time series forecasting model that considers some amount of redundancy is proposed, which combines an improved sparrow search algorithm (ISSA) and a least squares support vector regression machine regression (LSSVR) algorithm. The optimal values of the penalty factor and kernel function parameter of the LSSVR model are selected by ISSA, which improves the prediction accuracy and generalization performance of the forecasting model. A multistep decision optimization method under fluctuating coal price conditions is proposed, and the model prediction results are applied to the boundary optimization design process. Using the widely applied block model as the basis, a set of optimal production nested pits is obtained, allowing the realm design results to fit the coal price fluctuation trend and further enhance enterprise efficiency. The applicability and effectiveness of this method were verified by taking an ideal two-dimensional model and an inclined coal seam open-pit coal mine in Xinjiang as an example. |
| first_indexed | 2024-04-09T12:50:44Z |
| format | Article |
| id | doaj.art-a422ff318fed40d696226096a8fcd7d8 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T12:50:44Z |
| publishDate | 2023-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-a422ff318fed40d696226096a8fcd7d82023-05-14T11:14:35ZengNature PortfolioScientific Reports2045-23222023-05-0113112210.1038/s41598-023-34641-7Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction methodBo Cao0Shuai Wang1Runcai Bai2Bo Zhao3Qingyi Li4Mingjia Lv5Guangwei Liu6College of Mining, Liaoning Technical UniversityCollege of Mining, Liaoning Technical UniversityCollege of Mining, Liaoning Technical UniversityCollege of Mining, Liaoning Technical UniversityCollege of Mining, Liaoning Technical UniversityCollege of Mining, Liaoning Technical UniversityCollege of Mining, Liaoning Technical UniversityAbstract As an important link in the complex system engineering project of open pit mining, the quality of the boundary determines the performance of the project to a large extent. However, changes in economic indicators may raise doubts about the optimality of mining boundaries. In this article, a coal price time series forecasting model that considers some amount of redundancy is proposed, which combines an improved sparrow search algorithm (ISSA) and a least squares support vector regression machine regression (LSSVR) algorithm. The optimal values of the penalty factor and kernel function parameter of the LSSVR model are selected by ISSA, which improves the prediction accuracy and generalization performance of the forecasting model. A multistep decision optimization method under fluctuating coal price conditions is proposed, and the model prediction results are applied to the boundary optimization design process. Using the widely applied block model as the basis, a set of optimal production nested pits is obtained, allowing the realm design results to fit the coal price fluctuation trend and further enhance enterprise efficiency. The applicability and effectiveness of this method were verified by taking an ideal two-dimensional model and an inclined coal seam open-pit coal mine in Xinjiang as an example.https://doi.org/10.1038/s41598-023-34641-7 |
| spellingShingle | Bo Cao Shuai Wang Runcai Bai Bo Zhao Qingyi Li Mingjia Lv Guangwei Liu Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction method Scientific Reports |
| title | Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction method |
| title_full | Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction method |
| title_fullStr | Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction method |
| title_full_unstemmed | Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction method |
| title_short | Boundary optimization of inclined coal seam open-pit mine based on the ISSA–LSSVR coal price prediction method |
| title_sort | boundary optimization of inclined coal seam open pit mine based on the issa lssvr coal price prediction method |
| url | https://doi.org/10.1038/s41598-023-34641-7 |
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