{"id":"https://openalex.org/W2899217548","doi":"https://doi.org/10.1109/etfa.2018.8502473","title":"Causality-Based Thermal Prediction for Data Center","display_name":"Causality-Based Thermal Prediction for Data Center","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2899217548","doi":"https://doi.org/10.1109/etfa.2018.8502473","mag":"2899217548"},"language":"en","primary_location":{"id":"doi:10.1109/etfa.2018.8502473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2018.8502473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","raw_type":"proceedings-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/A5065363497","display_name":"Anurag Nandwana","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141791","display_name":"ABB (India)","ror":"https://ror.org/0461kck49","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210141791","https://openalex.org/I885143765"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Anurag Nandwana","raw_affiliation_strings":["ABB Corporate Research, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"ABB Corporate Research, Bangalore, India","institution_ids":["https://openalex.org/I4210141791"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075139633","display_name":"Rahul Kumar Vij","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141791","display_name":"ABB (India)","ror":"https://ror.org/0461kck49","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210141791","https://openalex.org/I885143765"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rahul Kumar Vij","raw_affiliation_strings":["ABB Corporate Research, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"ABB Corporate Research, Bangalore, India","institution_ids":["https://openalex.org/I4210141791"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059102913","display_name":"Divyasheel Sharma","orcid":"https://orcid.org/0000-0002-8479-8675"},"institutions":[{"id":"https://openalex.org/I4210141791","display_name":"ABB (India)","ror":"https://ror.org/0461kck49","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210141791","https://openalex.org/I885143765"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Divyasheel Sharma","raw_affiliation_strings":["ABB Corporate Research, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"ABB Corporate Research, Bangalore, India","institution_ids":["https://openalex.org/I4210141791"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065363497"],"corresponding_institution_ids":["https://openalex.org/I4210141791"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.1245458,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1297","last_page":"1304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9868000149726868,"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"}},"topics":[{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9868000149726868,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/granger-causality","display_name":"Granger causality","score":0.7592663764953613},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5084899663925171},{"id":"https://openalex.org/keywords/data-center","display_name":"Data center","score":0.5083157420158386},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.5070650577545166},{"id":"https://openalex.org/keywords/air-temperature","display_name":"Air temperature","score":0.4728660583496094},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.45181116461753845},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.43227237462997437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3981061577796936},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.34883642196655273},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.33988863229751587},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2905920743942261},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.24392762780189514},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.17296966910362244},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.08595538139343262}],"concepts":[{"id":"https://openalex.org/C129824826","wikidata":"https://www.wikidata.org/wiki/Q2630107","display_name":"Granger causality","level":2,"score":0.7592663764953613},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5084899663925171},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.5083157420158386},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.5070650577545166},{"id":"https://openalex.org/C2983363897","wikidata":"https://www.wikidata.org/wiki/Q845339","display_name":"Air temperature","level":2,"score":0.4728660583496094},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.45181116461753845},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.43227237462997437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3981061577796936},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.34883642196655273},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.33988863229751587},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2905920743942261},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.24392762780189514},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.17296966910362244},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.08595538139343262},{"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/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/etfa.2018.8502473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2018.8502473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1490576214","https://openalex.org/W1525651898","https://openalex.org/W1969083606","https://openalex.org/W2012359940","https://openalex.org/W2049053063","https://openalex.org/W2100238688","https://openalex.org/W2113762408","https://openalex.org/W2132917208","https://openalex.org/W2143457654","https://openalex.org/W2150291618","https://openalex.org/W2165612525","https://openalex.org/W2167588478","https://openalex.org/W2178225550","https://openalex.org/W2330098792","https://openalex.org/W2486285194","https://openalex.org/W2495101885","https://openalex.org/W2522710757","https://openalex.org/W2567018189","https://openalex.org/W4248240383","https://openalex.org/W6677043214"],"related_works":["https://openalex.org/W126301054","https://openalex.org/W4251195004","https://openalex.org/W4242807451","https://openalex.org/W2127540830","https://openalex.org/W2035792466","https://openalex.org/W2977645287","https://openalex.org/W4251418261","https://openalex.org/W1972675643","https://openalex.org/W2154758532","https://openalex.org/W4387163654"],"abstract_inverted_index":{"Changes":[0],"in":[1,4,88,119],"operating":[2],"conditions":[3],"a":[5,25,84,111,120,141],"data":[6,121,126],"center":[7,127],"lead":[8],"to":[9,34,37,65,81,93,108],"heating-up":[10],"of":[11,16,21,105],"IT":[12,61],"equipment":[13,62],"and":[14,74,117,158],"generation":[15],"hot-spots.":[17,40],"A":[18],"required":[19],"supply":[20,69,89,115],"cold":[22],"air":[23,68,114],"at":[24],"specific":[26],"temperature":[27,73],"with":[28,138],"an":[29,91,124],"adequate":[30],"flow":[31,75],"rate":[32],"needs":[33],"be":[35],"maintained":[36],"avoid":[38],"such":[39,83,110],"To":[41],"do":[42],"so,":[43],"appropriately":[44],"identified":[45],"Air":[46],"Control":[47],"Units":[48],"(ACUs)":[49],"that":[50,132,151],"have":[51,140],"the":[52,57,60,67,103,133,153,156],"best":[53],"causal":[54],"effect":[55,95],"on":[56,96],"cabinets":[58,118,139],"where":[59],"runs,":[63],"need":[64],"change":[66],"characteristics":[70],"(i.e.,":[71],"supply-air":[72],"rate).":[76],"Hence,":[77],"it":[78],"is":[79],"essential":[80],"determine":[82],"relationship":[85,112,148,154],"between":[86,113,149,155],"changes":[87],"from":[90],"ACU":[92],"its":[94],"cabinets.":[97,159],"In":[98],"this":[99],"paper,":[100],"we":[101,130],"study":[102],"use":[104],"Granger":[106,136],"Causality":[107,137],"identify":[109],"sources":[116],"center.":[122],"Using":[123],"industrial":[125],"simulator":[128],"(6SigmaRoom),":[129],"show":[131],"ACUs":[134,157],"exhibiting":[135],"time-series":[142],"inference":[143],"based":[144],"unidirectional":[145],"temporal":[146],"precedence":[147],"them":[150],"establishes":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
