{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T00:22:20Z","timestamp":1785025340526,"version":"3.55.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T00:00:00Z","timestamp":1772841600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:00:00Z","timestamp":1776297600000},"content-version":"vor","delay-in-days":40,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Shaanxi Provincial Department of Science and Technology Key R&D Program - Key Project - Qinchuan Original Industrial Innovation Cluster Zone \u201cFour Chains\u201d Integration","award":["Grant No.2025CY-JJQ-191"],"award-info":[{"award-number":["Grant No.2025CY-JJQ-191"]}]},{"name":"the Open Fund of State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining","award":["Grant No. SZQZ2025-2-011"],"award-info":[{"award-number":["Grant No. SZQZ2025-2-011"]}]},{"name":"the Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology","award":["Grant No. 2024yjrc171"],"award-info":[{"award-number":["Grant No. 2024yjrc171"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-42874-5","type":"journal-article","created":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T09:06:38Z","timestamp":1772874398000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Intelligent risk assessment and early warning for human\u2013machine\u2013environment coupling in coal preparation plants"],"prefix":"10.1038","volume":"16","author":[{"given":"Yuechuan","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxi","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinghui","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,7]]},"reference":[{"key":"42874_CR1","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1016\/j.enpol.2016.02.054","volume":"93","author":"H Chen","year":"2016","unstructured":"Chen, H., Feng, Q., Zhu, D., Han, S. & Long, R. Impact of rent-seeking on productivity in Chinese coal mine safety supervision: A simulation study. Energy Policy. 93, 315\u2013329. https:\/\/doi.org\/10.1016\/j.enpol.2016.02.054 (2016).","journal-title":"Energy Policy"},{"key":"42874_CR2","doi-asserted-by":"publisher","first-page":"102777","DOI":"10.1016\/j.resourpol.2022.102777","volume":"77","author":"Y Wang","year":"2022","unstructured":"Wang, Y. et al. Reform and development of coal mine safety in China: An analysis from government supervision, technical equipment, and miner education. Resour. Policy. 77, 102777. https:\/\/doi.org\/10.1016\/j.resourpol.2022.102777 (2022).","journal-title":"Resour. Policy"},{"key":"42874_CR3","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1016\/j.ssci.2011.08.040","volume":"50","author":"H Chen","year":"2012","unstructured":"Chen, H., Qi, H., Long, R. & Zhang, M. Research on 10-year tendency of China coal mine accidents and the characteristics of human factors. Saf. Sci. 50, 745\u2013750. https:\/\/doi.org\/10.1016\/j.ssci.2011.08.040 (2012).","journal-title":"Saf. Sci."},{"key":"42874_CR4","unstructured":"Jingdao, F. N., Zhenguo, Y. N., & Chuan, L. Exploration of intelligent coal mining key technology based on 5G technology. mtkxjs. 48. Available: https:\/\/www.mtkxjs.com.cn\/en\/article\/id\/3e1bc78d-ee2d-415c-a512-e250fa8bc575  (2020)."},{"key":"42874_CR5","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/j.ijmst.2018.06.005","volume":"29","author":"G Wang","year":"2019","unstructured":"Wang, G., Xu, Y. & Ren, H. Intelligent and ecological coal mining as well as clean utilization technology in China: Review and prospects. Int. J. Min. Sci. Technol. 29, 161\u2013169. https:\/\/doi.org\/10.1016\/j.ijmst.2018.06.005 (2019).","journal-title":"Int. J. Min. Sci. Technol."},{"key":"42874_CR6","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1007\/s40789-022-00491-3","volume":"9","author":"G Wang","year":"2022","unstructured":"Wang, G. et al. Research and practice of intelligent coal mine technology systems in China. Int. J. Coal Sci. Technol. 9, 24. https:\/\/doi.org\/10.1007\/s40789-022-00491-3 (2022).","journal-title":"Int. J. Coal Sci. Technol."},{"key":"42874_CR7","doi-asserted-by":"publisher","first-page":"11433","DOI":"10.3390\/app142311433","volume":"14","author":"A Luty\u0144ski","year":"2024","unstructured":"Luty\u0144ski, A. & Luty\u0144ski, M. Coal dust and methane as a hazard in coal preparation plants. Appl. Sci. 14, 11433. https:\/\/doi.org\/10.3390\/app142311433 (2024).","journal-title":"Appl. Sci."},{"key":"42874_CR8","doi-asserted-by":"publisher","first-page":"103524","DOI":"10.1016\/j.resourpol.2023.103524","volume":"82","author":"B Wu","year":"2023","unstructured":"Wu, B., Wang, J., Qu, B., Qi, P. & Meng, Y. Development, effectiveness, and deficiency of China\u2019s coal mine safety supervision system. Resour. Policy. 82, 103524. https:\/\/doi.org\/10.1016\/j.resourpol.2023.103524 (2023).","journal-title":"Resour. Policy"},{"key":"42874_CR9","doi-asserted-by":"publisher","unstructured":"Li, S., He, C., Lu, C., Xu, K. & Xue, G. Research on intelligent dual prevention mechanism and intelligent security control platform of coal mine. Coal Sci. Technol. 51, 464\u2013473. https:\/\/doi.org\/10.13199\/j.cnki.cst.2022-2155 (2023).","DOI":"10.13199\/j.cnki.cst.2022-2155"},{"key":"42874_CR10","doi-asserted-by":"publisher","first-page":"462","DOI":"10.3390\/ijerph15030462","volume":"15","author":"L Sanmiquel","year":"2018","unstructured":"Sanmiquel, L., Bascompta, M., Rossell, J. M., Anticoi, H. F. & Guash, E. Analysis of occupational accidents in underground and surface mining in Spain using data-mining techniques. Int. J. Environ. Res. Public Health. 15, 462. https:\/\/doi.org\/10.3390\/ijerph15030462 (2018).","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"42874_CR11","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1016\/j.fuel.2019.03.067","volume":"250","author":"M Rezaee","year":"2019","unstructured":"Rezaee, M., Rajagopalan, V. N. & Honaker, R. Q. Conceptual modifications of coal preparation plants to minimize potential environmental issues associated with coal waste disposal. Fuel 250, 352\u2013361. https:\/\/doi.org\/10.1016\/j.fuel.2019.03.067 (2019).","journal-title":"Fuel"},{"key":"42874_CR12","doi-asserted-by":"publisher","DOI":"10.1080\/19392699.2025.2584172","author":"J Lu","year":"2025","unstructured":"Lu, J. et al. Multi-modal intelligent fault detection of screening equipment using sparse sensing and deep visual analysis: Field application in coal preparation plants. Int. J. Coal Prep. Util. https:\/\/doi.org\/10.1080\/19392699.2025.2584172 (2025).","journal-title":"Int. J. Coal Prep. Util."},{"key":"42874_CR13","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/j.matpr.2023.06.012","volume":"90","author":"S Kumar","year":"2023","unstructured":"Kumar, S., Bhatkulkar, T. & Kane, P. FMEA and FTA of coal handling system of power plant. Mater. Today Proc. 90, 197\u2013200. (2023). https:\/\/doi.org\/10.1016\/j.matpr.2023.06.012","journal-title":"Mater. Today Proc."},{"key":"42874_CR14","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.jhazmat.2009.08.076","volume":"173","author":"J Dunj\u00f3","year":"2010","unstructured":"Dunj\u00f3, J., Fthenakis, V., V\u00edlchez, J. A. & Arnaldos, J. Hazard and operability (HAZOP) analysis. A literature review. J. Hazard. Mater. 173, 19\u201332. https:\/\/doi.org\/10.1016\/j.jhazmat.2009.08.076 (2010).","journal-title":"J. Hazard. Mater."},{"key":"42874_CR15","doi-asserted-by":"publisher","first-page":"918","DOI":"10.1016\/j.ssci.2011.08.003","volume":"50","author":"J Cheng","year":"2012","unstructured":"Cheng, J. & Yang, S. Data mining applications in evaluating mine ventilation system. Saf. Sci. 50, 918\u2013922. https:\/\/doi.org\/10.1016\/j.ssci.2011.08.003 (2012).","journal-title":"Saf. Sci."},{"key":"42874_CR16","doi-asserted-by":"publisher","first-page":"1861","DOI":"10.1002\/qre.3741","volume":"41","author":"M Kaushik","year":"2025","unstructured":"Kaushik, M. & Kumar, M. Employing best\u2013worst approach and distance-similarity measure based aggregation method in intuitionistic fuzzy fault tree analysis for risk assessment with application to coal dust explosion. Qual. Reliab. Eng. Int. 41, 1861\u20131876. https:\/\/doi.org\/10.1002\/qre.3741 (2025).","journal-title":"Qual. Reliab. Eng. Int."},{"key":"42874_CR17","doi-asserted-by":"publisher","first-page":"e0302044","DOI":"10.1371\/journal.pone.0302044","volume":"19","author":"M Liu","year":"2024","unstructured":"Liu, M., Wu, L. & Hou, M. Dynamic risk assessment of a coal slurry preparation system based on the structure-variable dynamic Bayesian network. PLOS ONE. 19, e0302044. https:\/\/doi.org\/10.1371\/journal.pone.0302044 (2024).","journal-title":"PLOS ONE"},{"key":"42874_CR18","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1080\/15623599.2018.1452098","volume":"19","author":"A Darko","year":"2019","unstructured":"Darko, A. et al. Review of application of analytic hierarchy process (AHP) in construction. Int. J. Constr. Manage. 19, 436\u2013452. https:\/\/doi.org\/10.1080\/15623599.2018.1452098 (2019).","journal-title":"Int. J. Constr. Manage."},{"key":"42874_CR19","doi-asserted-by":"publisher","first-page":"544","DOI":"10.1007\/s10653-025-02835-9","volume":"47","author":"W Zhao","year":"2025","unstructured":"Zhao, W. et al. Evaluation of ecological environment vulnerability in the huainan coal mining area based on the sensitivity-resilience-pressure model and analytic hierarchy process. Environ. Geochem. Health. 47, 544. https:\/\/doi.org\/10.1007\/s10653-025-02835-9 (2025).","journal-title":"Environ. Geochem. Health"},{"key":"42874_CR20","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/s40789-022-00516-x","volume":"9","author":"J Yang","year":"2022","unstructured":"Yang, J. et al. CNN coal and rock recognition method based on hyperspectral data. Int. J. Coal Sci. Technol. 9, 63. https:\/\/doi.org\/10.1007\/s40789-022-00516-x (2022).","journal-title":"Int. J. Coal Sci. Technol."},{"key":"42874_CR21","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.3390\/en12091735","volume":"12","author":"Y Pu","year":"2019","unstructured":"Pu, Y., Apel, D. B., Szmigiel, A. & Chen, J. Image recognition of coal and coal gangue using a convolutional neural network and transfer learning. Energies 12, 1735. https:\/\/doi.org\/10.3390\/en12091735 (2019).","journal-title":"Energies"},{"key":"42874_CR22","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.isprsjprs.2020.12.010","volume":"173","author":"T Kattenborn","year":"2021","unstructured":"Kattenborn, T., Leitloff, J., Schiefer, F. & Hinz, S. Review on convolutional neural networks (CNN) in vegetation remote sensing. ISPRS J. Photogramm. Remote Sens. 173, 24\u201349. https:\/\/doi.org\/10.1016\/j.isprsjprs.2020.12.010 (2021).","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"42874_CR23","doi-asserted-by":"publisher","first-page":"1066","DOI":"10.1016\/j.procs.2022.01.135","volume":"199","author":"P Jiang","year":"2022","unstructured":"Jiang, P., Ergu, D., Liu, F., Cai, Y. & Ma, B. A review of yolo algorithm developments. Proc. Comput. Sci. 199, 1066\u20131073. https:\/\/doi.org\/10.1016\/j.procs.2022.01.135 (2022).","journal-title":"Proc. Comput. Sci."},{"key":"42874_CR24","doi-asserted-by":"publisher","first-page":"9052","DOI":"10.3390\/s22239052","volume":"22","author":"Y Wang","year":"2022","unstructured":"Wang, Y. et al. A big coal block alarm detection method for scraper conveyor based on YOLO-BS. Sensors 22, 9052. https:\/\/doi.org\/10.3390\/s22239052 (2022).","journal-title":"Sensors"},{"key":"42874_CR25","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1007\/s11760-025-04787-0","volume":"19","author":"W Li","year":"2025","unstructured":"Li, W. et al. Enhanced YOLO architecture for real-time coal gangue detection with lightweight design. SIViP 19, 1199. https:\/\/doi.org\/10.1007\/s11760-025-04787-0 (2025).","journal-title":"SIViP"},{"key":"42874_CR26","doi-asserted-by":"publisher","first-page":"112573","DOI":"10.1016\/j.automatica.2025.112573","volume":"183","author":"R Ma","year":"2026","unstructured":"Ma, R., Hu, Z., Yang, R. & Wu, L. Aperiodic-sampled neural network controllers with closed-loop stability verifications. Automatica 183, 112573. https:\/\/doi.org\/10.1016\/j.automatica.2025.112573 (2026).","journal-title":"Automatica"},{"key":"42874_CR27","doi-asserted-by":"publisher","first-page":"112556","DOI":"10.1016\/j.automatica.2025.112556","volume":"183","author":"R Dinkla","year":"2026","unstructured":"Dinkla, R., Oomen, T., Mulders, S. P. & Van Wingerden, J-W. Closed-loop data-enabled predictive control and its equivalence with closed-loop subspace predictive control. Automatica 183, 112556. https:\/\/doi.org\/10.1016\/j.automatica.2025.112556 (2026).","journal-title":"Automatica"},{"key":"42874_CR28","doi-asserted-by":"publisher","first-page":"808","DOI":"10.1177\/09596518241302853","volume":"239","author":"Y Li","year":"2025","unstructured":"Li, Y., Zhu, Z., Li, X., Yang, C. & Lu, H. An improved \u03b5-greedy strategy based reinforcement learning for autonomous control of mining electric locomotives. Proc. Inst Mech. Eng. Part. I: J. Syst. Control Eng. 239, 808\u2013822. https:\/\/doi.org\/10.1177\/09596518241302853 (2025).","journal-title":"Proc. Inst. Mech. Eng. Part. I: J. Syst. Control Eng."},{"key":"42874_CR29","doi-asserted-by":"publisher","first-page":"4378","DOI":"10.1002\/rnc.5499","volume":"31","author":"I Mart\u00ednez-Forte","year":"2021","unstructured":"Mart\u00ednez-Forte, I. & Cervera, J. Accelerated quantitative feedback theory interval automatic loop shaping algorithm. Intl J. Robust. Nonlinear. 31, 4378\u20134396. https:\/\/doi.org\/10.1002\/rnc.5499 (2021).","journal-title":"Intl J. Robust. Nonlinear"},{"key":"42874_CR30","doi-asserted-by":"publisher","first-page":"1182","DOI":"10.4271\/2020-01-0017","volume":"02","author":"M Franke","year":"2020","unstructured":"Franke, M., Krause, S., Thoben, K-D., Himmler, A. & Hribernik, K. A. Adaptive test feedback loop: A modeling approach for checking side effects during test execution in advised explorative testing. SAE Int. J. Adv. Curr. Prac Mobil. 02, 1182\u20131188. https:\/\/doi.org\/10.4271\/2020-01-0017 (2020).","journal-title":"SAE Int. J. Adv. Curr. Prac Mobil."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-42874-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-42874-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-42874-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,19]],"date-time":"2026-04-19T11:01:47Z","timestamp":1776596507000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-42874-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,7]]},"references-count":30,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["42874"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-42874-5","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-8707910\/v1","asserted-by":"object"}]},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,7]]},"assertion":[{"value":"27 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"12503"}}