{"id":"https://openalex.org/W3133777092","doi":"https://doi.org/10.1109/tnsm.2021.3052093","title":"Alarm Prediction in Cellular Base Stations Using Data-Driven Methods","display_name":"Alarm Prediction in Cellular Base Stations Using Data-Driven Methods","publication_year":2021,"publication_date":"2021-02-25","ids":{"openalex":"https://openalex.org/W3133777092","doi":"https://doi.org/10.1109/tnsm.2021.3052093","mag":"3133777092"},"language":"en","primary_location":{"id":"doi:10.1109/tnsm.2021.3052093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnsm.2021.3052093","pdf_url":null,"source":{"id":"https://openalex.org/S173527311","display_name":"IEEE Transactions on Network and Service Management","issn_l":"1932-4537","issn":["1932-4537","2373-7379"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Network and Service Management","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/A5009173383","display_name":"Martin Boldt","orcid":"https://orcid.org/0000-0002-9316-4842"},"institutions":[{"id":"https://openalex.org/I52719799","display_name":"Blekinge Institute of Technology","ror":"https://ror.org/0093a8w51","country_code":"SE","type":"education","lineage":["https://openalex.org/I52719799"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Martin Boldt","raw_affiliation_strings":["Blekinge Institute of Technology, Karlskrona, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-9316-4842","affiliations":[{"raw_affiliation_string":"Blekinge Institute of Technology, Karlskrona, Sweden","institution_ids":["https://openalex.org/I52719799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025957480","display_name":"Selim \u0130ckin","orcid":"https://orcid.org/0000-0002-7594-2663"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Selim Ickin","raw_affiliation_strings":["Ericsson Research, Ericsson Research, Torshamnsgatan 23, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-7594-2663","affiliations":[{"raw_affiliation_string":"Ericsson Research, Ericsson Research, Torshamnsgatan 23, Sweden","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046863989","display_name":"Anton Borg","orcid":"https://orcid.org/0000-0002-8929-7220"},"institutions":[{"id":"https://openalex.org/I52719799","display_name":"Blekinge Institute of Technology","ror":"https://ror.org/0093a8w51","country_code":"SE","type":"education","lineage":["https://openalex.org/I52719799"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Anton Borg","raw_affiliation_strings":["Blekinge Institute of Technology, Karlskrona, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-8929-7220","affiliations":[{"raw_affiliation_string":"Blekinge Institute of Technology, Karlskrona, Sweden","institution_ids":["https://openalex.org/I52719799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015665629","display_name":"Valentin Kulyk","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Valentin Kulyk","raw_affiliation_strings":["Ericsson Research, Ericsson Research, Torshamnsgatan 23, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson Research, Ericsson Research, Torshamnsgatan 23, Sweden","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069619165","display_name":"J\u00f6rgen Gustafsson","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Jorgen Gustafsson","raw_affiliation_strings":["Ericsson Research, Ericsson Research, Torshamnsgatan 23, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson Research, Ericsson Research, Torshamnsgatan 23, Sweden","institution_ids":["https://openalex.org/I1306339040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5009173383"],"corresponding_institution_ids":["https://openalex.org/I52719799"],"apc_list":null,"apc_paid":null,"fwci":4.2712,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.9446815,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"18","issue":"2","first_page":"1925","last_page":"1933"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9868000149726868,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9868000149726868,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7834749221801758},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6961169242858887},{"id":"https://openalex.org/keywords/alarm","display_name":"ALARM","score":0.5922295451164246},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5775039792060852},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.5343906879425049},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5005524158477783},{"id":"https://openalex.org/keywords/performance-prediction","display_name":"Performance prediction","score":0.49619418382644653},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4819643199443817},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.4774094820022583},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4398805797100067},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4215550720691681},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35844671726226807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3186735510826111},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.21257299184799194},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.13447248935699463},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07906973361968994}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7834749221801758},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6961169242858887},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.5922295451164246},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5775039792060852},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.5343906879425049},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5005524158477783},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.49619418382644653},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4819643199443817},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.4774094820022583},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4398805797100067},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4215550720691681},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35844671726226807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3186735510826111},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.21257299184799194},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.13447248935699463},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07906973361968994},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnsm.2021.3052093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnsm.2021.3052093","pdf_url":null,"source":{"id":"https://openalex.org/S173527311","display_name":"IEEE Transactions on Network and Service Management","issn_l":"1932-4537","issn":["1932-4537","2373-7379"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Network and Service Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3812240757","display_name":null,"funder_award_id":"20140032","funder_id":"https://openalex.org/F4320307330","funder_display_name":"Knowledge Foundation"}],"funders":[{"id":"https://openalex.org/F4320307330","display_name":"Knowledge Foundation","ror":"https://ror.org/00v64cg28"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1491281150","https://openalex.org/W1517062113","https://openalex.org/W1526441817","https://openalex.org/W1565746575","https://openalex.org/W1570448133","https://openalex.org/W2009543464","https://openalex.org/W2016864600","https://openalex.org/W2026519996","https://openalex.org/W2037928371","https://openalex.org/W2061554433","https://openalex.org/W2080440878","https://openalex.org/W2096425971","https://openalex.org/W2158698691","https://openalex.org/W2289195472","https://openalex.org/W2737883091","https://openalex.org/W2809684781","https://openalex.org/W3003191277","https://openalex.org/W3026211003","https://openalex.org/W4234556776"],"related_works":["https://openalex.org/W3191198889","https://openalex.org/W4399767560","https://openalex.org/W2966986544","https://openalex.org/W2397087612","https://openalex.org/W2110529327","https://openalex.org/W153340049","https://openalex.org/W2803417426","https://openalex.org/W2371116970","https://openalex.org/W2802138742","https://openalex.org/W561355174"],"abstract_inverted_index":{"The":[0],"importance":[1],"of":[2,95,141,152,159,168,199],"cellular":[3,69],"networks":[4],"continuously":[5],"increases":[6],"as":[7],"we":[8],"assume":[9],"ubiquitous":[10],"connectivity":[11],"in":[12,147,184],"our":[13],"daily":[14],"lives.":[15],"As":[16],"a":[17,40,76,150,205],"result,":[18],"the":[19,91,114,128,136,139,180,191,197],"underlying":[20],"core":[21],"telecom":[22],"systems":[23],"have":[24],"very":[25],"high":[26,48,210],"reliability":[27,51,211],"and":[28,52,100,123,162,195,212],"availability":[29,53,213],"requirements,":[30],"that":[31,43,127,203],"are":[32,86,193],"sometimes":[33],"hard":[34],"to":[35,88,110,178,186],"meet.":[36],"This":[37],"study":[38],"presents":[39],"proactive":[41,206],"approach":[42,122],"could":[44],"aid":[45],"satisfying":[46],"these":[47],"requirements":[49],"on":[50],"by":[54],"predicting":[55,142],"future":[56],"base":[57,71,80],"station":[58,81],"alarms.":[59,82],"A":[60,117,171],"data":[61,77],"set":[62,78],"containing":[63,79],"231":[64],"internal":[65],"performance":[66,94],"measures":[67],"from":[68,107],"(4G)":[70],"stations":[72],"is":[73],"correlated":[74],"with":[75,149],"Next,":[83],"two":[84],"experiments":[85],"used":[87,177],"investigate":[89],"(i)":[90],"alarm":[92],"prediction":[93],"six":[96],"machine":[97],"learning":[98],"models,":[99],"(ii)":[101],"how":[102],"different":[103],"predict-ahead":[104],"times":[105],"(ranging":[106],"10":[108],"min":[109],"48":[111],"hours)":[112],"affect":[113],"predictive":[115],"performance.":[116,134],"10-fold":[118],"cross":[119],"validation":[120],"evaluation":[121],"statistical":[124],"analysis":[125],"suggested":[126],"Random":[129],"Forest":[130],"models":[131],"showed":[132],"best":[133],"Further,":[135],"results":[137,192],"indicate":[138,196],"feasibility":[140],"severe":[143],"alarms":[144],"one":[145],"hour":[146],"advance":[148],"precision":[151],"0.812":[153],"(\u00b10.022,":[154],"95":[155],"%":[156],"CI),":[157],"recall":[158],"0.619":[160],"(\u00b10.027)":[161],"F":[163],"<sub":[164],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[165],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[166],"-score":[167],"0.702":[169],"(\u00b10.022).":[170],"model":[172,188],"interpretation":[173],"package,":[174],"ELI5,":[175],"was":[176],"identify":[179],"most":[181],"influential":[182],"features":[183],"order":[185],"gain":[187],"insight.":[189],"Overall,":[190],"promising":[194],"potential":[198],"an":[200],"early-warning":[201],"system":[202],"enables":[204],"means":[207],"for":[208],"achieving":[209],"requirements.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
