{"id":"https://openalex.org/W2884184002","doi":"https://doi.org/10.1109/access.2018.2859756","title":"Call Detail Records Driven Anomaly Detection and Traffic Prediction in Mobile Cellular Networks","display_name":"Call Detail Records Driven Anomaly Detection and Traffic Prediction in Mobile Cellular Networks","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2884184002","doi":"https://doi.org/10.1109/access.2018.2859756","mag":"2884184002"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2859756","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2859756","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2859756","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061022840","display_name":"Kashif Sultan","orcid":"https://orcid.org/0000-0002-6194-9864"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kashif Sultan","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6194-9864","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051893714","display_name":"Hazrat Ali","orcid":"https://orcid.org/0000-0003-3058-5794"},"institutions":[{"id":"https://openalex.org/I16076960","display_name":"COMSATS University Islamabad","ror":"https://ror.org/00nqqvk19","country_code":"PK","type":"education","lineage":["https://openalex.org/I16076960"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Hazrat Ali","raw_affiliation_strings":["Department of Electrical Engineering, COMSATS University Islamabad, Abbottabad, Pakistan"],"raw_orcid":"https://orcid.org/0000-0003-3058-5794","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, COMSATS University Islamabad, Abbottabad, Pakistan","institution_ids":["https://openalex.org/I16076960"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040401781","display_name":"Zhongshan Zhang","orcid":"https://orcid.org/0000-0001-6454-4689"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongshan Zhang","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":13.4914,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.98633966,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"41728","last_page":"41737"},"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":0.9988999962806702,"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":0.9988999962806702,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8257983922958374},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7959098219871521},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6184805035591125},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.571210503578186},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5649970769882202},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.550270140171051},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.46428433060646057},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45106297731399536},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44628071784973145},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.44607192277908325},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44181716442108154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.428377240896225},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.41484004259109497},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0945076048374176}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8257983922958374},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7959098219871521},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6184805035591125},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.571210503578186},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5649970769882202},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.550270140171051},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.46428433060646057},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45106297731399536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44628071784973145},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.44607192277908325},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44181716442108154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.428377240896225},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.41484004259109497},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0945076048374176},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2018.2859756","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2859756","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1807.11545","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1807.11545","pdf_url":"https://arxiv.org/pdf/1807.11545","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:doaj.org/article:ae0aa140a4d441b1a3b1b765fe3ce503","is_oa":true,"landing_page_url":"https://doaj.org/article/ae0aa140a4d441b1a3b1b765fe3ce503","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 41728-41737 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2859756","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2859756","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5600000023841858,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G3058588409","display_name":null,"funder_award_id":"L172026","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G3189940716","display_name":"\u65f6\u7a7a\u4e00\u81f4\u6027\u7684\u65e0\u7ebf\u63a5\u5165\u7f51\u7edc\u67b6\u6784\u4e0e\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61431001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320323266","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1535235023","https://openalex.org/W1594523937","https://openalex.org/W2036514253","https://openalex.org/W2054692642","https://openalex.org/W2057301737","https://openalex.org/W2074978750","https://openalex.org/W2083879935","https://openalex.org/W2103253806","https://openalex.org/W2160160578","https://openalex.org/W2237031838","https://openalex.org/W2281611560","https://openalex.org/W2285154146","https://openalex.org/W2798056406","https://openalex.org/W2963008907","https://openalex.org/W3022458846","https://openalex.org/W6635593171","https://openalex.org/W6690278426"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"Mobile":[0],"networks":[1],"possess":[2],"information":[3,13],"about":[4],"the":[5,10,18,38,60,69,125,136,144,153,182,188],"users":[6],"as":[7,9,100,102],"well":[8,101],"network.":[11,70],"Such":[12],"is":[14],"useful":[15],"for":[16,97,173],"making":[17],"network":[19,32,121],"end-to-end":[20],"visible":[21],"and":[22,31,48,73,105,117,127,146,155,191],"intelligent.":[23],"Big":[24],"data":[25,46,64,112,130,185],"analytics":[26,47],"can":[27,92],"efficiently":[28],"analyze":[29],"user":[30],"information,":[33],"unearth":[34],"meaningful":[35],"insights":[36],"with":[37],"help":[39],"of":[40,75,89,138,143,152],"machine":[41,49,83],"learning":[42,84,189],"tools.":[43],"Utilizing":[44],"big":[45],"learning,":[50],"this":[51,132],"paper":[52],"contributes":[53],"in":[54,68,141],"three":[55],"ways.":[56],"First,":[57],"we":[58,77,91,108,134,161,179],"utilize":[59],"call":[61],"detail":[62],"records":[63],"to":[65,94,169],"detect":[66],"anomalies":[67],"For":[71],"authentication":[72],"verification":[74],"anomalies,":[76,90],"use":[78,162],"k-means":[79],"clustering,":[80],"an":[81,163],"unsupervised":[82],"algorithm.":[85],"Through":[86,176],"effective":[87],"detection":[88,104],"proceed":[93],"suitable":[95],"design":[96],"resource":[98],"distribution":[99],"fault":[103],"avoidance.":[106],"Second,":[107],"prepare":[109],"anomaly":[110,126,128,154,156,183],"free":[111,129,157,184],"by":[113],"removing":[114],"anomalous":[115,139],"activities":[116,140],"train":[118],"a":[119,174],"neural":[120],"model.":[122],"By":[123],"passing":[124],"through":[131],"model,":[133],"observe":[135,148],"effect":[137],"training":[142],"model":[145,168],"also":[147],"mean":[149],"square":[150],"error":[151],"data.":[158],"At":[159],"last,":[160],"autoregressive":[164],"integrated":[165],"moving":[166],"average":[167],"predict":[170],"future":[171],"traffic":[172],"user.":[175],"simple":[177],"visualization,":[178],"show":[180],"that":[181],"better":[186,193],"generalizes":[187],"models":[190],"performs":[192],"on":[194],"prediction":[195],"task.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
