Research on coal mine longwall face gas state analysis and safety warning strategy based on multi-sensor forecasting models
Intelligent computing is transforming safety inspection methods and response strategies in coal mines. Due to the significant safety hazards associated with mining excavation, this study proposes a multi-source data based predictive model for assessing gas risk and implementing countermeasures. By e...
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| Vydáno v: | Scientific reports Ročník 14; číslo 1; s. 13795 - 12 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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London
Nature Publishing Group UK
14.06.2024
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2045-2322, 2045-2322 |
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| Abstract | Intelligent computing is transforming safety inspection methods and response strategies in coal mines. Due to the significant safety hazards associated with mining excavation, this study proposes a multi-source data based predictive model for assessing gas risk and implementing countermeasures. By examining the patterns of gas dispersion at the longwall face, utilizing both temporal and spatial correlation, a predictive model is crafted that incorporates safety thresholds for gas concentrations, four-level early warning method and response strategy are devised by integrating weighted predictive confidence with these correlations. Initially tested using a public dataset from Poland, this method was later verified in coal mine in China. This paper discusses the validity and correlation of multi-source monitoring data in temporal and spatial correlation and proposes a risk warning mechanism based on it, which can be applied not only for safety warning but also for regulatory management. |
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| AbstractList | Intelligent computing is transforming safety inspection methods and response strategies in coal mines. Due to the significant safety hazards associated with mining excavation, this study proposes a multi-source data based predictive model for assessing gas risk and implementing countermeasures. By examining the patterns of gas dispersion at the longwall face, utilizing both temporal and spatial correlation, a predictive model is crafted that incorporates safety thresholds for gas concentrations, four-level early warning method and response strategy are devised by integrating weighted predictive confidence with these correlations. Initially tested using a public dataset from Poland, this method was later verified in coal mine in China. This paper discusses the validity and correlation of multi-source monitoring data in temporal and spatial correlation and proposes a risk warning mechanism based on it, which can be applied not only for safety warning but also for regulatory management. Intelligent computing is transforming safety inspection methods and response strategies in coal mines. Due to the significant safety hazards associated with mining excavation, this study proposes a multi-source data based predictive model for assessing gas risk and implementing countermeasures. By examining the patterns of gas dispersion at the longwall face, utilizing both temporal and spatial correlation, a predictive model is crafted that incorporates safety thresholds for gas concentrations, four-level early warning method and response strategy are devised by integrating weighted predictive confidence with these correlations. Initially tested using a public dataset from Poland, this method was later verified in coal mine in China. This paper discusses the validity and correlation of multi-source monitoring data in temporal and spatial correlation and proposes a risk warning mechanism based on it, which can be applied not only for safety warning but also for regulatory management.Intelligent computing is transforming safety inspection methods and response strategies in coal mines. Due to the significant safety hazards associated with mining excavation, this study proposes a multi-source data based predictive model for assessing gas risk and implementing countermeasures. By examining the patterns of gas dispersion at the longwall face, utilizing both temporal and spatial correlation, a predictive model is crafted that incorporates safety thresholds for gas concentrations, four-level early warning method and response strategy are devised by integrating weighted predictive confidence with these correlations. Initially tested using a public dataset from Poland, this method was later verified in coal mine in China. This paper discusses the validity and correlation of multi-source monitoring data in temporal and spatial correlation and proposes a risk warning mechanism based on it, which can be applied not only for safety warning but also for regulatory management. Abstract Intelligent computing is transforming safety inspection methods and response strategies in coal mines. Due to the significant safety hazards associated with mining excavation, this study proposes a multi-source data based predictive model for assessing gas risk and implementing countermeasures. By examining the patterns of gas dispersion at the longwall face, utilizing both temporal and spatial correlation, a predictive model is crafted that incorporates safety thresholds for gas concentrations, four-level early warning method and response strategy are devised by integrating weighted predictive confidence with these correlations. Initially tested using a public dataset from Poland, this method was later verified in coal mine in China. This paper discusses the validity and correlation of multi-source monitoring data in temporal and spatial correlation and proposes a risk warning mechanism based on it, which can be applied not only for safety warning but also for regulatory management. |
| ArticleNumber | 13795 |
| Author | Hu, Zuxiang Chang, Haoqian Meng, Xiangrui Wang, Xiangqian |
| Author_xml | – sequence: 1 givenname: Haoqian surname: Chang fullname: Chang, Haoqian email: haoqian.chang@durham.ac.uk organization: School of Economics and Management, Anhui University of Science & Technology – sequence: 2 givenname: Xiangrui surname: Meng fullname: Meng, Xiangrui organization: School of Economics and Management, Anhui University of Science & Technology – sequence: 3 givenname: Xiangqian surname: Wang fullname: Wang, Xiangqian email: xiqwang@aust.edu.cn organization: School of Economics and Management, Anhui University of Science & Technology – sequence: 4 givenname: Zuxiang surname: Hu fullname: Hu, Zuxiang organization: School of Economics and Management, Anhui University of Science & Technology |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38877166$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.4018/JDM.2019040104 10.1109/LCOMM.2021.3081593 10.1016/j.eswa.2019.113082 10.2991/ijcis.d.201214.001 10.1016/j.resourpol.2023.103802 10.1016/j.compind.2022.103783 10.1016/j.psep.2019.10.002 10.3390/ijerph16081406 10.1016/j.engappai.2017.06.002 10.1080/17480930.2015.1123599 10.1016/j.ijmst.2016.11.003 10.1016/j.psep.2017.02.023 10.3390/s21175730 10.3390/app132011369 10.1162/neco.1997.9.8.1735 10.1016/j.psep.2020.05.037 10.1016/j.energy.2021.120847 10.1007/s12613-019-1956-9 10.1007/s40789-022-00491-3 10.1016/j.psep.2022.12.077 10.1016/j.ress.2021.107433 10.1016/j.aei.2023.102275 10.1016/j.ins.2018.04.026 10.1007/s00603-022-03093-2 10.1007/s00477-023-02382-8 10.1016/j.psep.2022.08.065 10.2478/amns.2021.2.00299 10.1016/j.dib.2021.107457 10.1109/CAC48633.2019.8996314 |
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| Keywords | Mining safety Time series analysis Mining management engineering Warning strategy |
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| References | Hyder, Siau, Nah (CR8) 2019; 30 Tingjiang, Enyuan, Ke, Changfang (CR11) 2023; 85 Dindarloo, Siami-Irdemoosa (CR16) 2017; 31 Miao, Lv, Yu, Liu, Jiang (CR9) 2023; 171 Xie, Li, Wang (CR15) 2024; 59 Lei, Cheng, Wang, Ren, Tu (CR1) 2023; 56 Wang (CR10) 2022; 9 Wu, Xu, Wang, Long (CR36) 2021; 34 Diaz, Agioutantis, Hristopulos, Schafrik, Luxbacher (CR13) 2022; 39 Yang, Yu, Zhang, Li, Niu (CR24) 2021; 25 CR12 Xiang (CR3) 2014; 2014 Lai, Shao (CR33) 2023; 8 Liu, Lin, Fu, Zhu (CR7) 2020; 141 Shi, Wang, Zhang, Cheng, Zhao (CR32) 2017; 107 Zhang, Ai, Guo, Cui (CR17) 2021; 14 Du (CR23) 2023; 40 Ma (CR6) 2020; 27 Gao (CR18) 2023; 13 Qiao (CR19) 2021; 208 Kursunoglu (CR31) 2024; 1 Wu, Gao, Yang (CR14) 2020; 133 Liu, Gong, Yang, Chen (CR28) 2020; 143 Hochreiter, Schmidhuber (CR35) 1997; 9 Tutak, Brodny (CR21) 2019; 16 Ye (CR4) 2023; 144 Guo (CR2) 2021; 230 Ashish (CR27) 2017; 30 Cai, Wu, Zhou, Gao, Yu (CR20) 2021; 21 CR22 Vaswani (CR37) 2017; 30 Fan, Li, Luo, Du, Yang (CR5) 2017; 27 Janusz (CR25) 2017; 64 Kozielski, Sikora, Wróbel (CR26) 2021; 39 Zhang, Wang, Zhang, Li, Wang (CR30) 2022; 167 Diaz, Agioutantis, Hristopulos, Luxbacher, Schafrik (CR29) 2023; 37 Ślęzak (CR34) 2018; 451 Y Cai (64181_CR20) 2021; 21 W Lai (64181_CR33) 2023; 8 SR Dindarloo (64181_CR16) 2017; 31 G Wang (64181_CR10) 2022; 9 Y-K Ma (64181_CR6) 2020; 27 64181_CR12 Y Wu (64181_CR14) 2020; 133 W Xiang (64181_CR3) 2014; 2014 W Qiao (64181_CR19) 2021; 208 J Diaz (64181_CR13) 2022; 39 J Diaz (64181_CR29) 2023; 37 G Zhang (64181_CR30) 2022; 167 D Miao (64181_CR9) 2023; 171 A Vaswani (64181_CR37) 2017; 30 T Tingjiang (64181_CR11) 2023; 85 T Liu (64181_CR7) 2020; 141 Z Guo (64181_CR2) 2021; 230 N Kursunoglu (64181_CR31) 2024; 1 M Kozielski (64181_CR26) 2021; 39 Y Liu (64181_CR28) 2020; 143 Y Lei (64181_CR1) 2023; 56 64181_CR22 Z Du (64181_CR23) 2023; 40 X Yang (64181_CR24) 2021; 25 J Zhang (64181_CR17) 2021; 14 X Gao (64181_CR18) 2023; 13 S Hochreiter (64181_CR35) 1997; 9 C Fan (64181_CR5) 2017; 27 M Tutak (64181_CR21) 2019; 16 V Ashish (64181_CR27) 2017; 30 Z Ye (64181_CR4) 2023; 144 L Shi (64181_CR32) 2017; 107 D Ślęzak (64181_CR34) 2018; 451 H Wu (64181_CR36) 2021; 34 J Xie (64181_CR15) 2024; 59 A Janusz (64181_CR25) 2017; 64 Z Hyder (64181_CR8) 2019; 30 |
| References_xml | – volume: 1 start-page: 1 year: 2024 end-page: 17 ident: CR31 article-title: Fuzzy multi-criteria decision-making framework for controlling methane explosions in coal mines publication-title: Environ. Sci. Pollut. Res. – volume: 30 start-page: 1 year: 2017 ident: CR37 article-title: Attention is all you need publication-title: Adv. Neural Inf. Process. Syst. – ident: CR22 – volume: 30 start-page: 67 year: 2019 end-page: 79 ident: CR8 article-title: Artificial intelligence, machine learning, and autonomous technologies in mining industry publication-title: J. Database Manag. doi: 10.4018/JDM.2019040104 – volume: 25 start-page: 2579 year: 2021 end-page: 2583 ident: CR24 article-title: Minegps: Battery-free localization base station for coal mine environment publication-title: IEEE Commun. Lett. doi: 10.1109/LCOMM.2021.3081593 – volume: 143 start-page: 113082 year: 2020 ident: CR28 article-title: Dstp-rnn: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series prediction publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.113082 – volume: 14 start-page: 376 year: 2021 end-page: 385 ident: CR17 article-title: Research of synergy warning system for gas outburst based on entropy-weight Bayesian publication-title: Int. J. Comput. Intell. Syst. doi: 10.2991/ijcis.d.201214.001 – volume: 85 start-page: 103802 year: 2023 ident: CR11 article-title: Research on assisting coal mine hazard investigation for accident prevention through text mining and deep learning publication-title: Resour. Policy doi: 10.1016/j.resourpol.2023.103802 – volume: 144 start-page: 103783 year: 2023 ident: CR4 article-title: A digital twin approach for tunnel construction safety early warning and management publication-title: Comput. Ind. doi: 10.1016/j.compind.2022.103783 – volume: 133 start-page: 64 year: 2020 end-page: 72 ident: CR14 article-title: Prediction of coal and gas outburst: A method based on the bp neural network optimized by gasa publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2019.10.002 – volume: 16 start-page: 1406 year: 2019 ident: CR21 article-title: Predicting methane concentration in longwall regions using artificial neural networks publication-title: Int. J. Environ. Res. Public Health doi: 10.3390/ijerph16081406 – volume: 64 start-page: 83 year: 2017 end-page: 94 ident: CR25 article-title: Predicting seismic events in coal mines based on underground sensor measurements publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2017.06.002 – volume: 34 start-page: 22419 year: 2021 end-page: 22430 ident: CR36 article-title: Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting publication-title: Adv. Neural Inf. Process. Syst. – volume: 31 start-page: 105 year: 2017 end-page: 118 ident: CR16 article-title: Data mining in mining engineering: Results of classification and clustering of shovels failures data publication-title: Int. J. Mining Reclam. Environ. doi: 10.1080/17480930.2015.1123599 – ident: CR12 – volume: 27 start-page: 49 year: 2017 end-page: 55 ident: CR5 article-title: Coal and gas outburst dynamic system publication-title: Int. J. Mining Sci. Technol. doi: 10.1016/j.ijmst.2016.11.003 – volume: 107 start-page: 317 year: 2017 end-page: 333 ident: CR32 article-title: A risk assessment method to quantitatively investigate the methane explosion in underground coal mine publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2017.02.023 – volume: 21 start-page: 5730 year: 2021 ident: CR20 article-title: Early warning of gas concentration in coal mines production based on probability density machine publication-title: Sensors doi: 10.3390/s21175730 – volume: 40 start-page: 807 year: 2023 end-page: 818 ident: CR23 article-title: Response characteristics of gas concentration level in mining process and intelligent recognition method based on bi-lstm publication-title: Mining Metall. Explor. – volume: 13 start-page: 11369 year: 2023 ident: CR18 article-title: An agcrn algorithm for pressure prediction in an ultra-long mining face in a medium-thick coal seam in the northern Shaanxi area publication-title: China. Appl. Sci. doi: 10.3390/app132011369 – volume: 9 start-page: 1735 year: 1997 end-page: 1780 ident: CR35 article-title: Long short-term memory publication-title: Neural Comput. doi: 10.1162/neco.1997.9.8.1735 – volume: 141 start-page: 202 year: 2020 end-page: 214 ident: CR7 article-title: Modeling air leakage around gas extraction boreholes in mining-disturbed coal seams publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2020.05.037 – volume: 230 start-page: 120847 year: 2021 ident: CR2 article-title: Prediction of coalbed methane production based on deep learning publication-title: Energy doi: 10.1016/j.energy.2021.120847 – volume: 27 start-page: 872 year: 2020 end-page: 887 ident: CR6 article-title: Mechanism investigation on coal and gas outburst: An overview publication-title: Int. J. Miner. Metall. Mater. doi: 10.1007/s12613-019-1956-9 – volume: 9 start-page: 24 year: 2022 ident: CR10 article-title: Research and practice of intelligent coal mine technology systems in China publication-title: Int. J. Coal Sci. Technol. doi: 10.1007/s40789-022-00491-3 – volume: 171 start-page: 1 year: 2023 end-page: 17 ident: CR9 article-title: Research on coal mine hidden danger analysis and risk early warning technology based on data mining in china publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2022.12.077 – volume: 208 start-page: 107433 year: 2021 ident: CR19 article-title: Analysis and measurement of multifactor risk in underground coal mine accidents based on coupling theory publication-title: Reliab. Eng. Syst. Saf. doi: 10.1016/j.ress.2021.107433 – volume: 59 start-page: 102275 year: 2024 ident: CR15 article-title: A novel dt-based intelligent experiment method for complex industrial products publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2023.102275 – volume: 451 start-page: 112 year: 2018 end-page: 133 ident: CR34 article-title: A framework for learning and embedding multi-sensor forecasting models into a decision support system: A case study of methane concentration in coal mines publication-title: Inf. Sci. doi: 10.1016/j.ins.2018.04.026 – volume: 56 start-page: 363 year: 2023 end-page: 377 ident: CR1 article-title: Mechanisms of coal and gas outburst experiments: Implications for the energy principle of natural outbursts publication-title: Rock Mech. Rock Eng. doi: 10.1007/s00603-022-03093-2 – volume: 37 start-page: 2099 year: 2023 end-page: 2115 ident: CR29 article-title: Forecasting of methane gas in underground coal mines: Univariate versus multivariate time series modeling publication-title: Stoch. Environ. Res. Risk Assess. doi: 10.1007/s00477-023-02382-8 – volume: 167 start-page: 97 year: 2022 end-page: 111 ident: CR30 article-title: A comprehensive risk assessment method for coal and gas outburst in underground coal mines based on variable weight theory and uncertainty analysis publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2022.08.065 – volume: 8 start-page: 407 year: 2023 end-page: 418 ident: CR33 article-title: Projection of early warning identification of hazardous sources of gas explosion accidents in coal mines based on ntm deep learning network publication-title: Appl. Math. Nonlinear Sci. doi: 10.2478/amns.2021.2.00299 – volume: 39 start-page: 1961 year: 2022 end-page: 1982 ident: CR13 article-title: Time series modeling of methane gas in underground mines publication-title: Mining Metall. Explor. – volume: 39 start-page: 107457 year: 2021 ident: CR26 article-title: Data on methane concentration collected by underground coal mine sensors publication-title: Data Brief doi: 10.1016/j.dib.2021.107457 – volume: 30 start-page: 1 year: 2017 ident: CR27 article-title: Attention is all you need publication-title: Adv. Neural Inf. Process. Syst. – volume: 2014 start-page: 1 year: 2014 ident: CR3 article-title: Short-term coalmine gas concentration prediction based on wavelet transform and extreme learning machine publication-title: Math. Probl. Eng. – ident: 64181_CR12 – volume: 39 start-page: 107457 year: 2021 ident: 64181_CR26 publication-title: Data Brief doi: 10.1016/j.dib.2021.107457 – volume: 133 start-page: 64 year: 2020 ident: 64181_CR14 publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2019.10.002 – volume: 34 start-page: 22419 year: 2021 ident: 64181_CR36 publication-title: Adv. Neural Inf. Process. Syst. – volume: 208 start-page: 107433 year: 2021 ident: 64181_CR19 publication-title: Reliab. Eng. Syst. Saf. doi: 10.1016/j.ress.2021.107433 – volume: 31 start-page: 105 year: 2017 ident: 64181_CR16 publication-title: Int. J. Mining Reclam. Environ. doi: 10.1080/17480930.2015.1123599 – volume: 56 start-page: 363 year: 2023 ident: 64181_CR1 publication-title: Rock Mech. Rock Eng. doi: 10.1007/s00603-022-03093-2 – volume: 141 start-page: 202 year: 2020 ident: 64181_CR7 publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2020.05.037 – volume: 8 start-page: 407 year: 2023 ident: 64181_CR33 publication-title: Appl. Math. Nonlinear Sci. doi: 10.2478/amns.2021.2.00299 – volume: 2014 start-page: 1 year: 2014 ident: 64181_CR3 publication-title: Math. Probl. Eng. – volume: 59 start-page: 102275 year: 2024 ident: 64181_CR15 publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2023.102275 – ident: 64181_CR22 doi: 10.1109/CAC48633.2019.8996314 – volume: 21 start-page: 5730 year: 2021 ident: 64181_CR20 publication-title: Sensors doi: 10.3390/s21175730 – volume: 143 start-page: 113082 year: 2020 ident: 64181_CR28 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.113082 – volume: 13 start-page: 11369 year: 2023 ident: 64181_CR18 publication-title: China. Appl. Sci. doi: 10.3390/app132011369 – volume: 30 start-page: 67 year: 2019 ident: 64181_CR8 publication-title: J. Database Manag. doi: 10.4018/JDM.2019040104 – volume: 16 start-page: 1406 year: 2019 ident: 64181_CR21 publication-title: Int. J. Environ. Res. Public Health doi: 10.3390/ijerph16081406 – volume: 25 start-page: 2579 year: 2021 ident: 64181_CR24 publication-title: IEEE Commun. Lett. doi: 10.1109/LCOMM.2021.3081593 – volume: 1 start-page: 1 year: 2024 ident: 64181_CR31 publication-title: Environ. Sci. Pollut. Res. – volume: 9 start-page: 1735 year: 1997 ident: 64181_CR35 publication-title: Neural Comput. doi: 10.1162/neco.1997.9.8.1735 – volume: 27 start-page: 49 year: 2017 ident: 64181_CR5 publication-title: Int. J. Mining Sci. Technol. doi: 10.1016/j.ijmst.2016.11.003 – volume: 230 start-page: 120847 year: 2021 ident: 64181_CR2 publication-title: Energy doi: 10.1016/j.energy.2021.120847 – volume: 144 start-page: 103783 year: 2023 ident: 64181_CR4 publication-title: Comput. Ind. doi: 10.1016/j.compind.2022.103783 – volume: 27 start-page: 872 year: 2020 ident: 64181_CR6 publication-title: Int. J. Miner. Metall. Mater. doi: 10.1007/s12613-019-1956-9 – volume: 9 start-page: 24 year: 2022 ident: 64181_CR10 publication-title: Int. J. Coal Sci. Technol. doi: 10.1007/s40789-022-00491-3 – volume: 85 start-page: 103802 year: 2023 ident: 64181_CR11 publication-title: Resour. Policy doi: 10.1016/j.resourpol.2023.103802 – volume: 64 start-page: 83 year: 2017 ident: 64181_CR25 publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2017.06.002 – volume: 39 start-page: 1961 year: 2022 ident: 64181_CR13 publication-title: Mining Metall. Explor. – volume: 167 start-page: 97 year: 2022 ident: 64181_CR30 publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2022.08.065 – volume: 14 start-page: 376 year: 2021 ident: 64181_CR17 publication-title: Int. J. Comput. Intell. Syst. doi: 10.2991/ijcis.d.201214.001 – volume: 30 start-page: 1 year: 2017 ident: 64181_CR27 publication-title: Adv. Neural Inf. Process. Syst. – volume: 107 start-page: 317 year: 2017 ident: 64181_CR32 publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2017.02.023 – volume: 171 start-page: 1 year: 2023 ident: 64181_CR9 publication-title: Process Saf. Environ. Prot. doi: 10.1016/j.psep.2022.12.077 – volume: 30 start-page: 1 year: 2017 ident: 64181_CR37 publication-title: Adv. Neural Inf. Process. Syst. – volume: 37 start-page: 2099 year: 2023 ident: 64181_CR29 publication-title: Stoch. Environ. Res. Risk Assess. doi: 10.1007/s00477-023-02382-8 – volume: 40 start-page: 807 year: 2023 ident: 64181_CR23 publication-title: Mining Metall. Explor. – volume: 451 start-page: 112 year: 2018 ident: 64181_CR34 publication-title: Inf. Sci. doi: 10.1016/j.ins.2018.04.026 |
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