Citation: | WANG Jun, WANG Ranfeng, WEI Kai, et al. Multi step prediction of dense medium clean coal ash content based on time series alignment and TCNformer[J]. Journal of Mine Automation,2024,50(5):60-66. doi: 10.13272/j.issn.1671-251x.2023090007 |
[1] |
王然风,高建川,付翔. 智能化选煤厂架构及关键技术[J]. 工矿自动化,2019,45(7):28-32.
WANG Ranfeng,GAO Jianchuan,FU Xiang. Framework and key technologies of intelligent coal preparation plant[J]. Industry and Mine Automation,2019,45(7):28-32.
|
[2] |
张娟莉,康文泽,张相国,等. 桃山选煤厂精煤灰分预测的探讨[J]. 洁净煤技术,2007,13(4):15-17.
ZHANG Juanli,KANG Wenze,ZHANG Xiangguo,et al. Explore of clean coal ash content predicting of Taoshan Coal Washery[J]. Clean Coal Technology,2007,13(4):15-17.
|
[3] |
孔利利. 基于精煤灰分预测的重介悬浮液密度自动设定系统设计[J]. 选煤技术,2015(4):68-71.
KONG Lili. The design of dense medium suspension density setting system based on clean coal ash prediction[J]. Coal Preparation Technology,2015(4):68-71.
|
[4] |
张月飞,王伟,代伟. 重介分选过程产品指标在线预测方法研究[J]. 煤炭工程,2021,53(增刊1):108-111.
ZHANG Yuefei,WANG Wei,DAI Wei. On-line prediction of product indicators in dense medium coal separation[J]. Coal Engineering,2021,53(S1):108-111.
|
[5] |
李哲,孟巧荣,王然风,等. 基于EMD−RF算法的重介精煤灰分预测研究[J]. 煤炭工程,2023,55(10):174-179.
LI Zhe,MENG Qiaorong,WANG Ranfeng,et al. Predictive modeling of heavy refined coal ash based on EMD-RF algorithm[J]. Coal Engineering,2023,55(10):174-179.
|
[6] |
程凯,王然风,付翔. 基于EMD−LSTM的重介分选精煤灰分时间序列预测方法研究[J]. 煤炭工程,2022,54(2):133-139.
CHENG Kai,WANG Ranfeng,FU Xiang. Time series prediction method of clean coal ash content in dense medium separation based on EMD-LSTM[J]. Coal Engineering,2022,54(2):133-139.
|
[7] |
YIN Xianhui,NIU Zhanwen,HE Zhen,et al. Ensemble deep learning based semi-supervised soft sensor modeling method and its application on quality prediction for coal preparation process[J]. Advanced Engineering Informatics,2020,46. DOI: 10.1016/j.aei.2020.101136.
|
[8] |
ZHOU Chunxia,SUN Xiaolu,SHEN Yingsong,et al. Product quality prediction in dense medium coal preparation process based on recurrent neural network[J]. International Journal of Coal Preparation and Utilization,2024,44(3):291-308. doi: 10.1080/19392699.2023.2190098
|
[9] |
付建新,曹师,宋卫东,等. 考虑初始缺陷的超高矿柱蠕变分析及失稳滞后时间研究[J]. 中国矿业大学学报,2017,46(2):279-284.
FU Jianxin,CAO Shi,SONG Weidong,et al. Creep analysis and delay time of instability of ultrahigh pillar considering initial imperfections[J]. Journal of China University of Mining & Technology,2017,46(2):279-284.
|
[10] |
YOU Yalei,MENG Huan,DONG Jun,et al. Time-lag correlation between passive microwave measurements and surface precipitation and its impact on precipitation retrieval evaluation[J]. Geophysical Research Letters,2019,46(14):8415-8423. doi: 10.1029/2019GL083426
|
[11] |
EVTUSHEVSKY O M,KRAVCHENKO V O,HOOD L L,et al. Teleconnection between the central tropical Pacific and the Antarctic stratosphere:spatial patterns and time lags[J]. Climate Dynamics,2015,44(7/8):1841-1855.
|
[12] |
CHEN Jing,DING Ruilian,LIU Kangkang,et al. Collaboration between meteorology and public health:predicting the dengue epidemic in Guangzhou,China,by meteorological parameters[J]. Frontiers in Cellular and Infection Microbiology,2022,12. DOI: 10.3389/fcimb.2022.881745.
|
[13] |
VASWANI A,SHAZEER N,PARMAR N,et al. Attention is all you need[J]. Advances in Neural Information Processing Systems,2017,30:5998-6008.
|
[14] |
DEVLIN J,CHANG Mingwei,LEE K,et al. BERT:pre-training of deep bidirectional transformers for language understanding[EB/OL]. [2023-08-22]. https://arxiv.org/abs/1810.04805.
|
[15] |
DOSOVITSKIY A,BEYER L,KOLESNIKOV A,et al. An image is worth 16×16 words:transformers for image recognition at scale[EB/OL]. [2023-08-22]. https://arxiv.org/abs/2010.11929.
|
[16] |
BAI Shaojie,KOLTER J Z,KOLTUN V. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling[EB/OL]. [2023-08-22]. https://arxiv.org/abs/1803.01271.
|
[17] |
OORD A,DIELEMAN S,ZEN H,et al. WaveNet:a generative model for raw audio[EB/OL]. [2023-08-22]. https://arxiv.org/abs/1609.03499.
|
[18] |
YU F,KOLTUN V. Multi-scale context aggregation by dilated convolutions[EB/OL]. [2023-08-22]. https://arxiv.org/abs/1511.07122.
|
[19] |
WILLMOTT C J,MATSUURA K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance[J]. Climate Research,2005,30(1):79-82.
|
[20] |
KINGMA D P,BA J. Adam:a method for stochastic optimization[EB/OL]. [2023-08-22]. https://arxiv.org/abs/1412.6980.
|
[21] |
LOSHCHILOV I,HUTTER F. SGDR:stochastic gradient descent with warm restarts[EB/OL]. [2023-08-22]. https://arxiv.org/abs/1608.03983.
|