Prediction of longwall mining-induced stress in roof rock using LSTM neural network and transfer learning method
文献类型：期刊论文
| 作者 | Qin, Changkun1,2; Zhao, Wusheng1,2; Zhong, Kun1,2; Chen, Weizhong1 |
| 刊名 | ENERGY SCIENCE & ENGINEERING
 |
| 出版日期 | 2021-12-24 |
| 页码 | 14 |
| 关键词 | data missing LSTM mining-induced stress monitoring stress prediction transfer learning |
| DOI | 10.1002/ese3.1037 |
| 英文摘要 | Real-time monitoring of three-dimensional stress in the field is an effective approach to detect evolving stress in roof rock and to evaluate rock bursts risk. However, the sensors or data transmission cables may be damaged due to the volatile environment found in coal mines, which can lead to the loss of relevant monitoring data, and some critical information for rock burst prediction may be missed entirely. A number of methods that use historical data to predict missing data or future structural states have been proposed. However, the performance of these methods is poor when the training data are insufficient owing to lack of data. To address this issue, a methodology framework is proposed to predict the mining-induced stress when some monitoring data are missing. The framework uses a long short-term memory neural network integrated with the transfer learning method. The proposed method can transfer the knowledge learned from complete monitored data of adjacent sensor to target sensor to boost forecasting. A case study has been conducted to evaluate the method. The results show that the developed model can significantly improve the prediction performance for the target domain, which can be improved further by increasing the size of the target domain training data available. |
| 资助项目 | National Natural Science Foundation of China[51991393] ; National Natural Science Foundation of China[52079134] |
| WOS研究方向 | Energy & Fuels |
| 语种 | 英语 |
| WOS记录号 | WOS:000734009300001 |
| 出版者 | WILEY |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/30886]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Zhao, Wusheng |
| 作者单位 | 1.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Qin, Changkun,Zhao, Wusheng,Zhong, Kun,et al. Prediction of longwall mining-induced stress in roof rock using LSTM neural network and transfer learning method[J]. ENERGY SCIENCE & ENGINEERING,2021:14. |
| APA | Qin, Changkun,Zhao, Wusheng,Zhong, Kun,&Chen, Weizhong.(2021).Prediction of longwall mining-induced stress in roof rock using LSTM neural network and transfer learning method.ENERGY SCIENCE & ENGINEERING,14. |
| MLA | Qin, Changkun,et al."Prediction of longwall mining-induced stress in roof rock using LSTM neural network and transfer learning method".ENERGY SCIENCE & ENGINEERING (2021):14. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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