{"id":"https://openalex.org/W4249051918","doi":"https://doi.org/10.1504/ijie.2020.104654","title":"Call detail record-based traffic density analysis using global K-means clustering","display_name":"Call detail record-based traffic density analysis using global K-means clustering","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W4249051918","doi":"https://doi.org/10.1504/ijie.2020.104654"},"language":"en","primary_location":{"id":"doi:10.1504/ijie.2020.104654","doi":"https://doi.org/10.1504/ijie.2020.104654","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijie.2020.104654","pdf_url":null,"source":{"id":"https://openalex.org/S137885350","display_name":"International Journal of Intelligent Enterprise","issn_l":"1745-3232","issn":["1745-3232","1745-3240"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","jufo-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Enterprise","raw_type":"journal-article"},"volume":null,"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/A5003481294","display_name":"Suja Chandrasekharan Nair","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20497027","display_name":"Cochin University of Science and Technology","ror":"https://ror.org/00a4kqq17","country_code":"IN","type":"education","lineage":["https://openalex.org/I20497027"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suja Chandrasekharan Nair","raw_affiliation_strings":["School of Engineering, Cochin University of Science and Technology, Cochin 682021, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Cochin University of Science and Technology, Cochin 682021, India","institution_ids":["https://openalex.org/I20497027"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035477988","display_name":"M. Sudheep Elayidom","orcid":"https://orcid.org/0000-0003-3836-7425","observed_orcids":["https://orcid.org/0000-0003-3836-7425"]},"institutions":[{"id":"https://openalex.org/I20497027","display_name":"Cochin University of Science and Technology","ror":"https://ror.org/00a4kqq17","country_code":"IN","type":"education","lineage":["https://openalex.org/I20497027"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Sudheep Elayidom","raw_affiliation_strings":["School of Engineering, Cochin University of Science and Technology, Cochin 682021, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Cochin University of Science and Technology, Cochin 682021, India","institution_ids":["https://openalex.org/I20497027"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063059061","display_name":"Sasi Gopalan","orcid":"https://orcid.org/0000-0003-2332-8589","observed_orcids":["https://orcid.org/0000-0003-2332-8589"]},"institutions":[{"id":"https://openalex.org/I20497027","display_name":"Cochin University of Science and Technology","ror":"https://ror.org/00a4kqq17","country_code":"IN","type":"education","lineage":["https://openalex.org/I20497027"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sasi Gopalan","raw_affiliation_strings":["School of Engineering, Cochin University of Science and Technology, Cochin 682021, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Cochin University of Science and Technology, Cochin 682021, India","institution_ids":["https://openalex.org/I20497027"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20497027"],"apc_list":null,"apc_paid":null,"fwci":2.0075,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.87562444,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":"1/2/3","first_page":"176","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.38989999890327454,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.38989999890327454,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.2883000075817108,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.15279999375343323,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/call-detail-records","display_name":"call detail records","score":0.8939999938011169},{"id":"https://openalex.org/keywords/traffic-density-estimation","display_name":"traffic density estimation","score":0.9440000057220459},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"K-means clustering","score":0.8610000014305115},{"id":"https://openalex.org/keywords/k-nearest-neighbour-classification","display_name":"k-nearest neighbour classification","score":0.9350000023841858},{"id":"https://openalex.org/keywords/traffic-flow-dynamics","display_name":"traffic dynamics","score":0.7630000114440918},{"id":"https://openalex.org/keywords/urban-traffic","display_name":"urban traffic","score":0.9100000262260437}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7704899311065674},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7004067301750183},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.5742268562316895},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5614789724349976},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.4997389316558838},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4757130742073059},{"id":"https://openalex.org/C2781317605","wikidata":"https://www.wikidata.org/wiki/Q7832483","display_name":"Traffic analysis","level":2,"score":0.4416118562221527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2330114245414734},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1748889684677124},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1504/ijie.2020.104654","doi":"https://doi.org/10.1504/ijie.2020.104654","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijie.2020.104654","pdf_url":null,"source":{"id":"https://openalex.org/S137885350","display_name":"International Journal of Intelligent Enterprise","issn_l":"1745-3232","issn":["1745-3232","1745-3240"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","jufo-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Enterprise","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:ids:ijient:v:7:y:2020:i:1/2/3:p:176-187","doi":null,"is_oa":false,"landing_page_url":"http://www.inderscience.com/link.php?id=104654","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,"listed_in":[],"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/11","display_name":"Sustainable cities and communities","score":0.8787999749183655},{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6773999929428101}],"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/W1978166231","https://openalex.org/W2016185718","https://openalex.org/W2964468365","https://openalex.org/W2783660337","https://openalex.org/W2915012374","https://openalex.org/W4392308942","https://openalex.org/W3096856228","https://openalex.org/W2123007293","https://openalex.org/W2497615887","https://openalex.org/W2313910349"],"abstract_inverted_index":{"With":[0],"the":[1,7,28,37,47,60,67,70,79,83,94,111,114,118,121],"expanding":[2],"number":[3],"of":[4,49,69,82,120],"vehicles":[5],"on":[6],"road":[8],"is":[9,14],"creating":[10],"substantial":[11],"traffic":[12,29,50,61],"that":[13,126],"hard":[15],"to":[16,46,55,58,65,77],"control":[17],"and":[18,43,64,93,113,124],"maintain":[19],"safety,":[20],"particularly":[21],"in":[22,36],"extensive":[23],"urban":[24],"areas.":[25],"To":[26],"estimate":[27],"density":[30,62,80],"several":[31],"works":[32],"were":[33],"carried":[34],"out":[35],"past.":[38],"However,":[39],"they":[40],"are":[41,86],"inappropriate":[42],"expensive":[44],"due":[45],"dynamics":[48],"flow.":[51],"Here":[52],"we":[53,85],"intend":[54],"use":[56],"CDR":[57],"distinguish":[59],"location":[63,68],"track":[66],"mobile":[71],"user.":[72],"In":[73],"our":[74,127],"proposed":[75,101,122],"method":[76],"discover":[78],"scope":[81],"traffic,":[84],"using":[87],"two":[88],"algorithms":[89],"called":[90],"k-means":[91],"clustering":[92],"k":[95],"nearest":[96],"neighbour":[97],"classification":[98],"algorithms.":[99],"The":[100],"technique":[102,128],"will":[103],"be":[104],"tested":[105],"among":[106],"five":[107],"different":[108],"locations":[109],"during":[110],"weekdays":[112],"weekends,":[115],"which":[116],"show":[117,125],"noteworthiness":[119],"algorithm":[123],"has":[129],"high":[130],"accuracy.":[131]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2022-05-12T00:00:00"}
