{"id":"https://openalex.org/W4416632026","doi":"https://doi.org/10.5256/f1000research.157426.r217364","title":"Peer Review Report For: Accident severity prediction modeling for road safety using random forest algorithm: an analysis of Indian highways [version 2; peer review: 2 approved, 1 approved with reservations]","display_name":"Peer Review Report For: Accident severity prediction modeling for road safety using random forest algorithm: an analysis of Indian highways [version 2; peer review: 2 approved, 1 approved with reservations]","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4416632026","doi":"https://doi.org/10.5256/f1000research.157426.r217364"},"language":"en","primary_location":{"id":"doi:10.5256/f1000research.157426.r217364","doi":"https://doi.org/10.5256/f1000research.157426.r217364","is_oa":true,"landing_page_url":"https://doi.org/10.5256/f1000research.157426.r217364","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"University of Al-Qadisiyah","raw_type":"peer-review"},"volume":null,"type":"peer-review","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5256/f1000research.157426.r217364","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026915282","display_name":"Humera Khanum","orcid":"https://orcid.org/0000-0003-2689-6370","observed_orcids":["https://orcid.org/0000-0003-2689-6370"]},"institutions":[{"id":"https://openalex.org/I110360157","display_name":"Lovely Professional University","ror":"https://ror.org/00et6q107","country_code":"IN","type":"education","lineage":["https://openalex.org/I110360157"]},{"id":"https://openalex.org/I244572783","display_name":"Symbiosis International University","ror":"https://ror.org/005r2ww51","country_code":"IN","type":"education","lineage":["https://openalex.org/I244572783"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Humera Khanum","raw_affiliation_strings":["Civil Engineering Department, Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, Maharashtra, 412115","School of Civil Engineering, Lovely Professional University, Phagwara, Punjab, 1444411"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Civil Engineering Department, Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, Maharashtra, 412115","institution_ids":["https://openalex.org/I244572783"]},{"raw_affiliation_string":"School of Civil Engineering, Lovely Professional University, Phagwara, Punjab, 1444411","institution_ids":["https://openalex.org/I110360157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101398461","display_name":"Anshul Garg","orcid":"https://orcid.org/0000-0002-7759-9408","observed_orcids":["https://orcid.org/0000-0002-7759-9408"]},"institutions":[{"id":"https://openalex.org/I110360157","display_name":"Lovely Professional University","ror":"https://ror.org/00et6q107","country_code":"IN","type":"education","lineage":["https://openalex.org/I110360157"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anshul Garg","raw_affiliation_strings":["School of Civil Engineering, Lovely Professional University, Phagwara, Punjab, 1444411"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Lovely Professional University, Phagwara, Punjab, 1444411","institution_ids":["https://openalex.org/I110360157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055077774","display_name":"Mir Iqbal Faheem","orcid":"https://orcid.org/0000-0003-1674-4883","observed_orcids":["https://orcid.org/0000-0003-1674-4883"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mir Iqbal Faheem","raw_affiliation_strings":["Civil Engineering Department, Deccan College of Engineering and Technology, Hyderabad, Telangana, 500001"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Civil Engineering Department, Deccan College of Engineering and Technology, Hyderabad, Telangana, 500001","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026915282"],"corresponding_institution_ids":["https://openalex.org/I110360157","https://openalex.org/I244572783"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9970999956130981,"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/T10370","display_name":"Traffic and Road Safety","score":0.9970999956130981,"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/T12406","display_name":"IoT and GPS-based Vehicle Safety Systems","score":0.0010999999940395355,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T13527","display_name":"Transportation Systems and Logistics","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/traffic-accident-severity","display_name":"traffic accident severity","score":0.7400000095367432},{"id":"https://openalex.org/keywords/road-safety","display_name":"road safety","score":0.8389999866485596},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.7480000257492065},{"id":"https://openalex.org/keywords/crash-severity-prediction","display_name":"accident severity prediction","score":0.7319999933242798},{"id":"https://openalex.org/keywords/indian-highways","display_name":"Indian highways","score":0.902999997138977},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.5120000243186951},{"id":"https://openalex.org/keywords/accident-prevention","display_name":"accident prevention","score":0.5950000286102295},{"id":"https://openalex.org/keywords/traffic-accident-statistics","display_name":"traffic accident statistics","score":0.5450000166893005}],"concepts":[{"id":"https://openalex.org/C2780289543","wikidata":"https://www.wikidata.org/wiki/Q424630","display_name":"Accident (philosophy)","level":2,"score":0.5519000291824341},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3977000117301941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36649999022483826},{"id":"https://openalex.org/C3018122277","wikidata":"https://www.wikidata.org/wiki/Q9687","display_name":"Road accident","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.31049999594688416},{"id":"https://openalex.org/C2778521444","wikidata":"https://www.wikidata.org/wiki/Q3444700","display_name":"Forest road","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C3017944768","wikidata":"https://www.wikidata.org/wiki/Q1450463","display_name":"Poison control","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C2984003776","wikidata":"https://www.wikidata.org/wiki/Q6764307","display_name":"Marine safety","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.25929999351501465},{"id":"https://openalex.org/C2780591428","wikidata":"https://www.wikidata.org/wiki/Q2493120","display_name":"Accident analysis","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C77595967","wikidata":"https://www.wikidata.org/wiki/Q3151013","display_name":"Forensic engineering","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5256/f1000research.157426.r217364","doi":"https://doi.org/10.5256/f1000research.157426.r217364","is_oa":true,"landing_page_url":"https://doi.org/10.5256/f1000research.157426.r217364","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"University of Al-Qadisiyah","raw_type":"peer-review"},{"id":"doi:10.5256/f1000research.157426.r217364","doi":"https://doi.org/10.5256/f1000research.157426.r217364","is_oa":true,"landing_page_url":"https://doi.org/10.5256/f1000research.157426.r217364","pdf_url":null,"source":{"id":"https://openalex.org/S7407050752","display_name":"Faculty of 1000 Research Ltd","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.5256/f1000research.157426.r217364","doi":"https://doi.org/10.5256/f1000research.157426.r217364","is_oa":true,"landing_page_url":"https://doi.org/10.5256/f1000research.157426.r217364","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"University of Al-Qadisiyah","raw_type":"peer-review"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7246000170707703},{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6773999929428101}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Background:":[0],"Road":[1],"accidents":[2],"claim":[3],"around":[4],"1.35":[5],"million":[6],"lives":[7],"annually,":[8],"with":[9,148,164,184,253],"countries":[10],"like":[11],"India":[12,19],"facing":[13],"a":[14,63,92,138,149,158,246],"significant":[15],"impact.":[16],"In":[17],"2019,":[18],"reported":[20],"449,002":[21],"road":[22,265],"accidents,":[23],"causing":[24],"151,113":[25],"deaths":[26],"and":[27,37,49,87,98,104,111,125,137,191,216,229,255,258,269],"451,361":[28],"injuries.":[29],"Accident":[30],"severity":[31,69,183],"modeling":[32],"helps":[33],"understand":[34],"contributing":[35],"factors":[36],"develop":[38,62],"preventive":[39],"strategies.":[40],"AI":[41],"models,":[42],"such":[43],"as":[44],"random":[45,75,93,159,176],"forest,":[46],"offer":[47],"adaptability":[48],"higher":[50],"predictive":[51,64],"accuracy":[52,103,134,170,186],"compared":[53],"to":[54,61],"traditional":[55],"statistical":[56],"models.":[57],"This":[58],"study":[59],"aims":[60],"model":[65,101,116,130,179,231,234],"for":[66],"traffic":[67,181],"accident":[68,182,217,237,270],"on":[70,144,171,187,193],"Indian":[71],"highways":[72],"using":[73,102],"the":[74,100,145,188,194,203,211,214,240],"forest":[76,94,160,177],"algorithm.":[77],"Methods:":[78],"A":[79],"multi-step":[80],"methodology":[81],"was":[82,162],"employed,":[83],"involving":[84],"data":[85,248],"collection":[86],"preparation,":[88],"feature":[89],"selection,":[90],"training":[91,146,189],"model,":[95],"tuning":[96],"parameters,":[97,166],"evaluating":[99],"F1":[105],"score.":[106],"Data":[107],"sources":[108],"included":[109],"MoRTH":[110,254],"NHAI.":[112],"Results:":[113],"The":[114,129,175,233],"classification":[115],"had":[117],"hyperparameters":[118],"\u2018max":[119,122],"depth\u2019:":[120],"10,":[121],"features\u2019:":[123],"\u2018sqrt\u2019,":[124],"\u2018n":[126],"estimators\u2019:":[127],"100.":[128],"achieved":[131],"an":[132],"overall":[133],"of":[135,142,153,213,242],"67%":[136,185],"weighted":[139],"average":[140,151],"F1-score":[141,152],"0.64":[143],"set,":[147,196],"macro":[150],"0.53.":[154],"Using":[155],"grid":[156],"search,":[157],"Classifier":[161],"fitted":[163],"optimal":[165],"resulting":[167],"in":[168,202,251],"41.47%":[169,192],"test":[172,195],"data.":[173],"Conclusions:":[174],"classifier":[178],"predicted":[180],"set":[190],"suggesting":[197],"possible":[198],"bias":[199],"or":[200,219],"imbalance":[201,228],"dataset.":[204],"No":[205],"clear":[206],"patterns":[207],"were":[208],"found":[209],"between":[210],"day":[212],"week":[215],"occurrence":[218],"severity.":[220],"Performance":[221],"can":[222,263],"be":[223],"improved":[224],"by":[225],"addressing":[226],"dataset":[227],"refining":[230],"hyperparameters.":[232],"often":[235],"underestimated":[236],"severity,":[238],"highlighting":[239],"influence":[241],"external":[243],"factors.":[244],"Adopting":[245],"sophisticated":[247],"recording":[249],"system":[250],"line":[252],"IRC":[256],"guidelines":[257],"integrating":[259],"machine":[260],"learning":[261],"techniques":[262],"enhance":[264],"safety":[266],"modeling,":[267],"decision-making,":[268],"prevention":[271],"efforts.":[272]},"counts_by_year":[],"updated_date":"2026-09-09T07:26:56.047234","created_date":"2025-10-10T00:00:00"}