Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network
Abstract The transport truck is one of the important equipment for open-pit mines, and predicting the truck's fault time is of great significance in improving the economic benefits of open-pit mines. In this paper, we discuss the reason for the large prediction error of the exponential smoothin...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-45675-2 |
| _version_ | 1797636861751984128 |
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| author | Wei Liu Jiayang Sun Jinbiao Huang Guangwei Liu Runcai Bai |
| author_facet | Wei Liu Jiayang Sun Jinbiao Huang Guangwei Liu Runcai Bai |
| author_sort | Wei Liu |
| collection | DOAJ |
| description | Abstract The transport truck is one of the important equipment for open-pit mines, and predicting the truck's fault time is of great significance in improving the economic benefits of open-pit mines. In this paper, we discuss the reason for the large prediction error of the exponential smoothing method. Then, we propose a novel nonlinear exponential smoothing method (ESNN) for predicting the truck's fault time, and demonstrate the equivalence between our approach and the neural network structure. Finally, based on the augmented Lagrange function, the solving method of ESNN is proposed. We conduct experiments on real-world datasets and our results demonstrate the effectiveness of ESNN in comparison to existing state-of-the-art methods. Our approach makes it easier for maintenance personnel to predict fault situations in advance and provides a basis for enterprises to develop preventive maintenance plans. |
| first_indexed | 2024-03-11T12:41:19Z |
| format | Article |
| id | doaj.art-02c9270d6ca14e82b9f7b4e95cb50e9e |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-11T12:41:19Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-02c9270d6ca14e82b9f7b4e95cb50e9e2023-11-05T12:17:29ZengNature PortfolioScientific Reports2045-23222023-10-011311910.1038/s41598-023-45675-2Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural networkWei Liu0Jiayang Sun1Jinbiao Huang2Guangwei Liu3Runcai Bai4College of Science, Liaoning Technical UniversityCollege of Science, Liaoning Technical UniversityCollege of Mines, Liaoning Technical UniversityCollege of Mines, Liaoning Technical UniversityLiaoning Academy of Mineral Resources Development and Utilization Technology and Equipment, Liaoning Technical UniversityAbstract The transport truck is one of the important equipment for open-pit mines, and predicting the truck's fault time is of great significance in improving the economic benefits of open-pit mines. In this paper, we discuss the reason for the large prediction error of the exponential smoothing method. Then, we propose a novel nonlinear exponential smoothing method (ESNN) for predicting the truck's fault time, and demonstrate the equivalence between our approach and the neural network structure. Finally, based on the augmented Lagrange function, the solving method of ESNN is proposed. We conduct experiments on real-world datasets and our results demonstrate the effectiveness of ESNN in comparison to existing state-of-the-art methods. Our approach makes it easier for maintenance personnel to predict fault situations in advance and provides a basis for enterprises to develop preventive maintenance plans.https://doi.org/10.1038/s41598-023-45675-2 |
| spellingShingle | Wei Liu Jiayang Sun Jinbiao Huang Guangwei Liu Runcai Bai Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network Scientific Reports |
| title | Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network |
| title_full | Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network |
| title_fullStr | Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network |
| title_full_unstemmed | Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network |
| title_short | Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network |
| title_sort | prediction method for the truck s fault time in open pit mines based on exponential smoothing neural network |
| url | https://doi.org/10.1038/s41598-023-45675-2 |
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