{"id":"https://openalex.org/W2973796261","doi":"https://doi.org/10.4018/ijaci.2019100105","title":"Driving Behavior Evaluation Model Base on Big Data From Internet of Vehicles","display_name":"Driving Behavior Evaluation Model Base on Big Data From Internet of Vehicles","publication_year":2019,"publication_date":"2019-09-20","ids":{"openalex":"https://openalex.org/W2973796261","doi":"https://doi.org/10.4018/ijaci.2019100105","mag":"2973796261"},"language":"en","primary_location":{"id":"doi:10.4018/ijaci.2019100105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijaci.2019100105","pdf_url":null,"source":{"id":"https://openalex.org/S51041755","display_name":"International Journal of Ambient Computing and Intelligence","issn_l":"1941-6237","issn":["1941-6237","1941-6245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Ambient Computing and Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041664460","display_name":"Ruru Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruru Hao","raw_affiliation_strings":["Chang'an University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chang'an University, Xi'an, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052806976","display_name":"Hangzheng Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I6507939","display_name":"China United Network Communications Group (China)","ror":"https://ror.org/028w99c90","country_code":"CN","type":"company","lineage":["https://openalex.org/I6507939"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangzheng Yang","raw_affiliation_strings":["Chinaunicom Software Xi'an Branch, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinaunicom Software Xi'an Branch, Xi'an, China","institution_ids":["https://openalex.org/I6507939"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100359926","display_name":"Zhou Zhou","orcid":"https://orcid.org/0000-0002-6490-8945"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou Zhou","raw_affiliation_strings":["Chang'an University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chang'an University, Xi'an, China","institution_ids":["https://openalex.org/I25355098"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3444,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.88632767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"10","issue":"4","first_page":"78","last_page":"95"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"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/T12095","display_name":"Vehicle emissions and performance","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/computer-science","display_name":"Computer science","score":0.7749388217926025},{"id":"https://openalex.org/keywords/fuel-efficiency","display_name":"Fuel efficiency","score":0.7701330184936523},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7575733661651611},{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.6486309170722961},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.5445657968521118},{"id":"https://openalex.org/keywords/fuel-cells","display_name":"Fuel cells","score":0.47467541694641113},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.4043494164943695},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3536662459373474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23491430282592773},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.21404221653938293},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08138084411621094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7749388217926025},{"id":"https://openalex.org/C45882903","wikidata":"https://www.wikidata.org/wiki/Q5042317","display_name":"Fuel efficiency","level":2,"score":0.7701330184936523},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7575733661651611},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.6486309170722961},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.5445657968521118},{"id":"https://openalex.org/C2987658370","wikidata":"https://www.wikidata.org/wiki/Q180253","display_name":"Fuel cells","level":2,"score":0.47467541694641113},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.4043494164943695},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3536662459373474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23491430282592773},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.21404221653938293},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08138084411621094},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijaci.2019100105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijaci.2019100105","pdf_url":null,"source":{"id":"https://openalex.org/S51041755","display_name":"International Journal of Ambient Computing and Intelligence","issn_l":"1941-6237","issn":["1941-6237","1941-6245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Ambient Computing and Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jaci00:v:10:y:2019:i:4:p:78-95","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJACI.2019100105","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8700000047683716,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1832740374","https://openalex.org/W1969899752","https://openalex.org/W1977364734","https://openalex.org/W1992419399","https://openalex.org/W2007227052","https://openalex.org/W2012880677","https://openalex.org/W2016985433","https://openalex.org/W2019794065","https://openalex.org/W2056798162","https://openalex.org/W2067457993","https://openalex.org/W2079755609","https://openalex.org/W2087668941","https://openalex.org/W2091400818","https://openalex.org/W2153233077","https://openalex.org/W2261406529","https://openalex.org/W2528456768","https://openalex.org/W2572765888","https://openalex.org/W2747246333","https://openalex.org/W2771833153","https://openalex.org/W2782755540","https://openalex.org/W2787926350","https://openalex.org/W2790882261","https://openalex.org/W2799370386"],"related_works":["https://openalex.org/W3176449234","https://openalex.org/W2807508722","https://openalex.org/W3012802245","https://openalex.org/W2353158678","https://openalex.org/W2767235736","https://openalex.org/W4225278791","https://openalex.org/W2045002201","https://openalex.org/W584449260","https://openalex.org/W2971352445","https://openalex.org/W3118438776"],"abstract_inverted_index":{"This":[0],"article":[1],"attempts":[2],"to":[3,50,70,159],"evaluate":[4,128],"whether":[5,138],"a":[6,15,107],"driving":[7,16,78,83,95,110,130,140],"behavior":[8,17,84,96,111,131,141],"is":[9,142],"fuel-efficient.":[10,143],"To":[11],"solve":[12],"this":[13,23],"problem,":[14],"evaluation":[18,112,136],"model":[19,113,117,126,156],"was":[20,68,114,118],"proposed":[21,155],"in":[22],"article.":[24],"First,":[25],"the":[26,39,72,121,129,139,149,154],"operating":[27,60],"data":[28,32],"and":[29,91,133],"fuel":[30,51,93,108],"consumption":[31,94],"of":[33,58,82,137,153],"five":[34],"trucks":[35],"were":[36,53,85],"obtained":[37],"from":[38,55],"vehicle":[40,59],"networking":[41],"system.":[42],"Four":[43],"characteristic":[44,74],"parameters,":[45],"which":[46],"are":[47],"closely":[48],"related":[49],"consumption,":[52],"extracted":[54],"19":[56],"sets":[57],"data.":[61],"Then,":[62],"K-means":[63],"clustering":[64,98,101],"combined":[65],"with":[66,120],"DBSCAN":[67],"adopted":[69],"cluster":[71],"four":[73],"parameters":[75],"into":[76],"different":[77],"behaviors.":[79],"Three":[80],"types":[81],"labeled":[86,122],"respectively":[87],"as":[88],"low,":[89],"medium":[90],"high":[92],"after":[97],"analysis.":[99],"The":[100,116,124,144],"accuracy":[102,151],"rate":[103,152],"reached":[104],"79.7%.":[105],"Finally,":[106],"consumption-oriented":[109],"established.":[115],"trained":[119,125],"samples.":[123],"can":[127,157],"online":[132],"gives":[134],"an":[135],"test":[145],"results":[146],"show":[147],"that":[148],"prediction":[150],"reach":[158],"77.13%.":[160]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":5}],"updated_date":"2026-06-11T06:19:23.411458","created_date":"2025-10-10T00:00:00"}
