{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T00:53:06Z","timestamp":1776473586265,"version":"3.51.2"},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52304226"],"award-info":[{"award-number":["52304226"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Hunan Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2025JJ60311"],"award-info":[{"award-number":["2025JJ60311"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.aei.2026.104704","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T21:10:53Z","timestamp":1776460253000},"page":"104704","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["Causal analysis of radon distribution and anomalous source localization in underground ventilation systems"],"prefix":"10.1016","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3704-3739","authenticated-orcid":false,"given":"De","family":"Huang","sequence":"first","affiliation":[]},{"given":"Ziming","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yanlin","family":"Huang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9490-1322","authenticated-orcid":false,"given":"Yonghong","family":"Liu","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.aei.2026.104704_b0005","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1097\/01.ede.0000152522.80261.e3","article-title":"Residential radon and risk of lung cancer: a combined analysis of 7 north American Case-Control Studies","volume":"16","author":"Krewski","year":"2005","journal-title":"Epidemiology"},{"key":"10.1016\/j.aei.2026.104704_b0010","doi-asserted-by":"crossref","unstructured":"S. Darby, D. Hill, A. Auvinen, J.M. Barros-Dios, H. Baysson, F. Bochicchio, H. Deo, R. Falk, F. Forastiere, M. Hakama, I. Heid, L. Kreienbrock, M. Kreuzer, F. Lagarde, I. M\u00e4kel\u00e4inen, C. Muirhead, W. Oberaigner, G. Pershagen, A. Ruano-Ravina, E. Ruosteenoja, A.S. Rosario, M. Tirmarche, L. Tom\u00e1scaron;ek, E. Whitley, H.-E. Wichmann, R. Doll, Radon in homes and risk of lung cancer: collaborative analysis of individual data from 13 European case-control studies, BMJ 330 (2005) 223. https:\/\/doi.org\/10.1136\/bmj.38308.477650.63.","DOI":"10.1136\/bmj.38308.477650.63"},{"key":"10.1016\/j.aei.2026.104704_b0015","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1136\/oemed-2025-110297","article-title":"Updated cancer mortality among uranium miners on the Colorado Plateau: interactions of radon exposure with smoking and temporal factors","volume":"82","author":"Schubauer-Berigan","year":"2025","journal-title":"Occup. Environ. Med."},{"key":"10.1016\/j.aei.2026.104704_b0020","doi-asserted-by":"crossref","first-page":"1877","DOI":"10.1007\/s11869-021-01064-0","article-title":"Radiation hazards and lifetime risk assessment related to indoor and outdoor air inhalation using a passive detection technique","volume":"14","author":"Al-Shboul","year":"2021","journal-title":"Air Qual. Atmosphere Health"},{"key":"10.1016\/j.aei.2026.104704_b0025","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.1016\/j.apradiso.2011.06.009","article-title":"A comprehensive review of radon emanation measurements for mineral, rock, soil, mill tailing and fly ash","volume":"69","author":"Sakoda","year":"2011","journal-title":"Appl. Radiat. Isot."},{"key":"10.1016\/j.aei.2026.104704_b0030","article-title":"Radon transport from soil to air and Monte-Carlo simulation","volume":"227","author":"Muhammad","year":"2022","journal-title":"J. Atmospheric Sol.-Terr. Phys."},{"key":"10.1016\/j.aei.2026.104704_b0035","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1111\/1755-6724.15323","article-title":"Distribution Characteristics and Genetic Mechanisms of Geothermal Radon Mineral Water in Shandong Province","volume":"99","author":"Hu","year":"2025","journal-title":"Acta Geol. Sin. - Engl. Ed."},{"key":"10.1016\/j.aei.2026.104704_b0040","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1186\/s12302-021-00507-w","article-title":"Radiological survey on radon entry path in an underground mine and implementation of an optimized mitigation system","volume":"33","author":"Shahrokhi","year":"2021","journal-title":"Environ. Sci. Eur."},{"key":"10.1016\/j.aei.2026.104704_b0045","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.5194\/nhess-11-1179-2011","article-title":"Short-term 222Rn activity concentration changes in underground spaces with limited air exchange with the atmosphere","volume":"11","author":"Fija\u0142kowska-Lichwa","year":"2011","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"10.1016\/j.aei.2026.104704_b0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.jconhyd.2025.104602","article-title":"Numerical simulation of flow field and radon concentration distribution in large-scale roadways during drivage","volume":"273","author":"Lv","year":"2025","journal-title":"J. Contam. Hydrol."},{"key":"10.1016\/j.aei.2026.104704_b0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.radphyschem.2024.111977","article-title":"Evaluation of radiation dose associated with underground uranium mining activities in east Singhbhum, Jharkhand, India","volume":"223","author":"Sahu","year":"2024","journal-title":"Radiat. Phys. Chem."},{"key":"10.1016\/j.aei.2026.104704_b0060","doi-asserted-by":"crossref","first-page":"2222","DOI":"10.1016\/j.net.2023.02.020","article-title":"Fuzzy optimization of radon reduction by ventilation system in uranium mine","volume":"55","author":"Zhang","year":"2023","journal-title":"Nucl. Eng. Technol."},{"key":"10.1016\/j.aei.2026.104704_b0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.gexplo.2025.107867","article-title":"Indoor radon and its relationship with rock uranium concentration in western Liguria (Italy)","volume":"278","author":"Bonorino","year":"2025","journal-title":"J. Geochem. Explor."},{"key":"10.1016\/j.aei.2026.104704_b0070","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1007\/s41365-023-01275-3","article-title":"Reference device for calibration of radon exhalation rate measuring instruments and its performance","volume":"34","author":"Li","year":"2023","journal-title":"Nucl. Sci. Tech."},{"key":"10.1016\/j.aei.2026.104704_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhazmat.2025.137121","article-title":"Preparation and radon exhalation characteristics of fracture granite similar materials in Beishan underground research laboratory","volume":"487","author":"Wang","year":"2025","journal-title":"J. Hazard. Mater."},{"key":"10.1016\/j.aei.2026.104704_b0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.scs.2020.102599","article-title":"A study on the three-dimensional unsteady state of indoor radon diffusion under different ventilation conditions","volume":"66","author":"Xie","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"10.1016\/j.aei.2026.104704_b0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijheh.2021.113742","article-title":"Determination of optimal ventilation rates in educational environment in terms of radon dosimetry","volume":"234","author":"Dovjak","year":"2021","journal-title":"Int. J. Hyg. Environ. Health"},{"key":"10.1016\/j.aei.2026.104704_b0090","doi-asserted-by":"crossref","first-page":"2861","DOI":"10.1007\/s10967-025-10029-x","article-title":"Experimental study on the efficiency of calcium lignosulfonate-modified red clay for radon mitigation","volume":"334","author":"Liu","year":"2025","journal-title":"J. Radioanal. Nucl. Chem."},{"key":"10.1016\/j.aei.2026.104704_b0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2021.150800","article-title":"Identification of sources with abnormal radon exhalation rates based on radon concentrations in underground environments","volume":"807","author":"Huang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.aei.2026.104704_b0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103356","article-title":"Identification of stochastic disturbance sources of air doors in mine ventilation systems","volume":"65","author":"Liu","year":"2025","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104704_b0105","doi-asserted-by":"crossref","first-page":"4307","DOI":"10.1007\/s00477-023-02509-x","article-title":"Exploring the efficacy of machine learning models for predicting soil radon exhalation rates","volume":"37","author":"Al-Shboul","year":"2023","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"10.1016\/j.aei.2026.104704_b0110","doi-asserted-by":"crossref","first-page":"22140","DOI":"10.1038\/s41598-025-08108-w","article-title":"Edaphic and meteorological parameters as determinants of radon exhalation and its environmental implication in peruvian agroecosystems","volume":"15","author":"P\u00e9rez","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.aei.2026.104704_b0115","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.jenvrad.2019.03.003","article-title":"Automated anomalous behaviour detection in soil radon gas prior to earthquakes using computational intelligence techniques","volume":"203","author":"Tareen","year":"2019","journal-title":"J. Environ. Radioact."},{"key":"10.1016\/j.aei.2026.104704_b0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2025.147285","article-title":"Hybrid machine learning solutions for mitigating climate-induced productivity losses in sustainable construction management","volume":"538","author":"Shehadeh","year":"2026","journal-title":"J. Clean. Prod."},{"key":"10.1016\/j.aei.2026.104704_b0125","first-page":"1","article-title":"Enhancing risk prediction in high-rise construction: explainable artificial intelligence enabled probabilistic approach","author":"Alshboul","year":"2026","journal-title":"Int. J. Constr. Manag."},{"key":"10.1016\/j.aei.2026.104704_b0130","doi-asserted-by":"crossref","DOI":"10.1061\/JCEMD4.COENG-16001","article-title":"Adaptive Integration of BIM and Navisworks for Real-Time Clash Detection using the XGBoost Algorithm","volume":"152","author":"Alshboul","year":"2026","journal-title":"J. Constr. Eng. Manag."},{"key":"10.1016\/j.aei.2026.104704_b0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111761","article-title":"Enhancing occupational safety in Construction: Predictive analytics using advanced ensemble machine learning algorithms","volume":"159","author":"Shehadeh","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.aei.2026.104704_b0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.envpol.2023.122440","article-title":"Unraveling the complex interplay between soil characteristics and radon surface exhalation rates through machine learning models and multivariate analysis","volume":"336","author":"Al-Shboul","year":"2023","journal-title":"Environ. Pollut."},{"key":"10.1016\/j.aei.2026.104704_b0145","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.94.052201","article-title":"Information flow and causality as rigorous notions ab initio","volume":"94","author":"Liang","year":"2016","journal-title":"Phys. Rev. E"},{"key":"10.1016\/j.aei.2026.104704_b0150","doi-asserted-by":"crossref","DOI":"10.1063\/1.5010253","article-title":"Causation and information flow with respect to relative entropy","volume":"28","author":"Liang","year":"2018","journal-title":"Chaos Interdiscip. J. Nonlinear Sci."},{"key":"10.1016\/j.aei.2026.104704_b0155","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1038\/s41586-024-08328-6","article-title":"Accurate predictions on small data with a tabular foundation model","volume":"637","author":"Hollmann","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.aei.2026.104704_b0160","series-title":"Adv","first-page":"1877","article-title":"Language Models are Few-Shot Learners","author":"Brown","year":"2020"},{"key":"10.1016\/j.aei.2026.104704_b0165","doi-asserted-by":"crossref","first-page":"2052","DOI":"10.1109\/TCST.2012.2233476","article-title":"Direct Causality Detection via the transfer Entropy Approach","volume":"21","author":"Duan","year":"2013","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"10.1016\/j.aei.2026.104704_b0170","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.90.052150","article-title":"Unraveling the cause-effect relation between time series","volume":"90","author":"Liang","year":"2014","journal-title":"Phys. Rev. E"},{"key":"10.1016\/j.aei.2026.104704_b0175","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.92.022126","article-title":"Normalizing the causality between time series","volume":"92","author":"Liang","year":"2015","journal-title":"Phys. Rev. E"},{"key":"10.1016\/j.aei.2026.104704_b0180","doi-asserted-by":"crossref","first-page":"6537","DOI":"10.1109\/TII.2025.3567381","article-title":"An Integrated distributed Fault Diagnosis Framework for Large-Scale Industrial Processes based on Spatio\u2013Temporal Causal Analysis","volume":"21","author":"Hua","year":"2025","journal-title":"IEEE Trans. Ind. Inform."},{"key":"10.1016\/j.aei.2026.104704_b0185","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112346","article-title":"A deep spatio-temporal architecture for dynamic ECN analysis with Granger causality based causal discovery","volume":"172","author":"Xu","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.aei.2026.104704_b0190","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1109\/TDSC.2024.3403653","article-title":"Sliver: a Scalable Slicing-based Verification for Information Flow Security","volume":"22","author":"Rao","year":"2025","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"10.1016\/j.aei.2026.104704_b0195","doi-asserted-by":"crossref","DOI":"10.1063\/5.0283758","article-title":"Diversity and similarity of information transfers and flows in continuous-time stochastic systems","volume":"35","author":"Smirnov","year":"2025","journal-title":"Chaos Interdiscip. J. Nonlinear Sci."},{"key":"10.1016\/j.aei.2026.104704_b0200","first-page":"1","article-title":"Causal Discovery for Rolling Bearing Fault under Missing Data: from the Perspective of Causal effect and Information Flow","volume":"74","author":"Ding","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.aei.2026.104704_b0205","doi-asserted-by":"crossref","first-page":"679","DOI":"10.3390\/e23060679","article-title":"Normalized Multivariate Time Series Causality Analysis and Causal Graph Reconstruction","volume":"23","author":"Liang","year":"2021","journal-title":"Entropy"},{"key":"10.1016\/j.aei.2026.104704_b0210","series-title":"Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms, Washington","author":"Rosenblatt","year":"1962"}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003964?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003964?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T00:17:53Z","timestamp":1776471473000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034626003964"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":42,"alternative-id":["S1474034626003964"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104704","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Causal analysis of radon distribution and anomalous source localization in underground ventilation systems","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104704","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104704"}}