{"id":"https://openalex.org/W7122494912","doi":"https://doi.org/10.46873/2300-3960.1511","title":"Forecast of mining fatalities using machine learning algorithms","display_name":"Forecast of mining fatalities using machine learning algorithms","publication_year":2026,"publication_date":"2026-11-05","ids":{"openalex":"https://openalex.org/W7122494912","doi":"https://doi.org/10.46873/2300-3960.1511"},"language":"en","primary_location":{"id":"doi:10.46873/2300-3960.1511","doi":"https://doi.org/10.46873/2300-3960.1511","is_oa":true,"landing_page_url":"https://doi.org/10.46873/2300-3960.1511","pdf_url":null,"source":{"id":"https://openalex.org/S2764831130","display_name":"Journal of Sustainable Mining","issn_l":"2300-3960","issn":["2300-3960","2543-4950"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","ddh","doaj","dongbi-c","jufo-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/I3020398883","host_organization_name":"Central Mining Institute","host_organization_lineage":["https://openalex.org/I3020398883"],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sustainable Mining","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.46873/2300-3960.1511","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119938124","display_name":"Enoch Nii-Okai","orcid":"https://orcid.org/0009-0007-0024-0273","observed_orcids":["https://orcid.org/0009-0007-0024-0273"]},"institutions":[{"id":"https://openalex.org/I11957088","display_name":"Michigan Technological University","ror":"https://ror.org/0036rpn28","country_code":"US","type":"education","lineage":["https://openalex.org/I11957088"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Enoch Nii-Okai","raw_affiliation_strings":["Michigan Technological University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan Technological University","institution_ids":["https://openalex.org/I11957088"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5119938124"],"corresponding_institution_ids":["https://openalex.org/I11957088"],"apc_list":null,"apc_paid":null,"fwci":3.1308,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85763034,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"25","issue":"3","first_page":"547","last_page":"405"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14091","display_name":"Industrial and Mining Safety","score":0.9526000022888184,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14091","display_name":"Industrial and Mining Safety","score":0.9526000022888184,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14368","display_name":"Evaluation and Optimization Models","score":0.013899999670684338,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.009700000286102295,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mining-fatalities","display_name":"mining fatalities","score":0.9959999918937683},{"id":"https://openalex.org/keywords/occupational-safety","display_name":"occupational safety","score":0.6290000081062317},{"id":"https://openalex.org/keywords/mortality-prediction","display_name":"mortality prediction","score":0.7360000014305115},{"id":"https://openalex.org/keywords/mining-industry","display_name":"mining industry","score":0.5619999766349792},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"gradient boosting","score":0.8050000071525574},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9909999966621399},{"id":"https://openalex.org/keywords/ensemble-methods","display_name":"ensemble methods","score":0.6420000195503235},{"id":"https://openalex.org/keywords/shap","display_name":"SHAP","score":0.7279999852180481},{"id":"https://openalex.org/keywords/fatality-rate","display_name":"fatality rate","score":0.777999997138977}],"concepts":[{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.7074000239372253},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6912000179290771},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6888999938964844},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.657800018787384},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6029999852180481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5756000280380249},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.477400004863739},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4104999899864197},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41040000319480896},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C189285262","wikidata":"https://www.wikidata.org/wiki/Q1332350","display_name":"Multicollinearity","level":3,"score":0.3165999948978424},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.31310001015663147},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C32224588","wikidata":"https://www.wikidata.org/wiki/Q7250175","display_name":"Proper linear model","level":4,"score":0.3061000108718872},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.301800012588501},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2912999987602234},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.2865000069141388},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.2840000092983246},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27790001034736633},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2651999890804291},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.46873/2300-3960.1511","doi":"https://doi.org/10.46873/2300-3960.1511","is_oa":true,"landing_page_url":"https://doi.org/10.46873/2300-3960.1511","pdf_url":null,"source":{"id":"https://openalex.org/S2764831130","display_name":"Journal of Sustainable Mining","issn_l":"2300-3960","issn":["2300-3960","2543-4950"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","ddh","doaj","dongbi-c","jufo-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/I3020398883","host_organization_name":"Central Mining Institute","host_organization_lineage":["https://openalex.org/I3020398883"],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sustainable Mining","raw_type":"journal-article"},{"id":"doi:10.2139/ssrn.6045294","doi":"https://doi.org/10.2139/ssrn.6045294","is_oa":true,"landing_page_url":"https://doi.org/10.2139/ssrn.6045294","pdf_url":null,"source":{"id":"https://openalex.org/S4210172589","display_name":"SSRN Electronic Journal","issn_l":"1556-5068","issn":["1556-5068"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1318003438","host_organization_name":"RELX Group (Netherlands)","host_organization_lineage":["https://openalex.org/I1318003438"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.46873/2300-3960.1511","doi":"https://doi.org/10.46873/2300-3960.1511","is_oa":true,"landing_page_url":"https://doi.org/10.46873/2300-3960.1511","pdf_url":null,"source":{"id":"https://openalex.org/S2764831130","display_name":"Journal of Sustainable Mining","issn_l":"2300-3960","issn":["2300-3960","2543-4950"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","ddh","doaj","dongbi-c","jufo-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/I3020398883","host_organization_name":"Central Mining Institute","host_organization_lineage":["https://openalex.org/I3020398883"],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sustainable Mining","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6240000128746033},{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.48510000109672546}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4390653902","https://openalex.org/W4412345522","https://openalex.org/W3089220272","https://openalex.org/W3043651989","https://openalex.org/W4414760403","https://openalex.org/W7010832124","https://openalex.org/W2985627000","https://openalex.org/W4392119448","https://openalex.org/W2990555792","https://openalex.org/W3134963253"],"abstract_inverted_index":{"Mining":[0],"industry":[1],"plays":[2],"a":[3,100],"crucial":[4],"role":[5],"in":[6,32,167,179],"economic":[7],"development":[8],"but":[9],"is":[10],"often":[11],"accompanied":[12],"by":[13,151],"notable":[14],"occupational":[15],"hazards,":[16],"including":[17,60],"fatalities.":[18],"This":[19],"research":[20],"investigates":[21],"the":[22,33,45,123,129,133,159,180],"application":[23],"of":[24,125,140,143,147,161],"machine":[25,162],"learning":[26],"techniques":[27],"to":[28,41,80,104,193],"predict":[29],"mining":[30,181],"fatalities":[31],"United":[34],"States":[35],"using":[36,112],"historical":[37],"data":[38],"from":[39,44],"1983":[40],"2023,":[42],"sourced":[43],"National":[46],"Institute":[47],"for":[48,175],"Occupational":[49],"Safety":[50],"and":[51,54,74,86,98,122,145,153,171],"Health":[52],"(NIOSH)":[53],"FRED":[55],"Economic":[56],"Data.":[57],"Predictive":[58],"models":[59],"Random":[61],"Forest":[62],"(RF),":[63],"Gradient":[64],"Boosting":[65],"(GB),":[66],"Decision":[67],"Tree":[68],"(DT),":[69],"Multiple":[70],"Linear":[71,75],"Regression":[72,76],"(MLR),":[73],"(LR),":[77],"were":[78],"employed":[79,192],"assess":[81],"relationships":[82],"between":[83],"operational":[84],"parameters":[85],"annual":[87],"fatality":[88,101],"counts.":[89],"The":[90],"dataset":[91],"was":[92,110,191],"thoroughly":[93],"preprocessed,":[94],"addressing":[95],"missing":[96],"values":[97],"deriving":[99],"rate":[102],"metric":[103],"improve":[105],"predictive":[106,135],"accuracy.":[107],"Model":[108],"performance":[109],"evaluated":[111],"Mean":[113,118],"Absolute":[114],"Error":[115,120],"(MAE),":[116],"Root":[117],"Squared":[119],"(RMSE),":[121],"Coefficient":[124],"Determination":[126],"(R\u00b2).":[127],"Among":[128],"models,":[130],"GB":[131],"achieved":[132],"highest":[134],"accuracy,":[136],"with":[137],"an":[138],"MAE":[139],"7.85,":[141],"RMSE":[142],"10.04,":[144],"R\u00b2":[146],"0.903,":[148],"followed":[149],"closely":[150],"RF":[152],"LR":[154],"approaches.":[155],"These":[156],"findings":[157],"highlight":[158],"effectiveness":[160],"learning,":[163],"especially":[164],"ensemble":[165],"methods,":[166],"modeling":[168],"complex":[169],"patterns":[170],"offering":[172],"valuable":[173],"insights":[174,198],"improving":[176],"safety":[177],"outcomes":[178],"sector.":[182],"To":[183],"support":[184],"interpretability,":[185],"SHapley":[186],"Additive":[187],"exPlanations":[188],"(SHAP)":[189],"analysis":[190],"explain":[194],"feature":[195],"contributions,":[196],"providing":[197],"into":[199],"how":[200],"key":[201],"variables":[202],"influenced":[203],"model":[204],"predictions.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-01-13T00:00:00"}