{"id":"https://openalex.org/W4385196187","doi":"https://doi.org/10.1145/3583133.3596431","title":"Optimizing Telemetry Signal Influence for Power Consumption Prediction","display_name":"Optimizing Telemetry Signal Influence for Power Consumption Prediction","publication_year":2023,"publication_date":"2023-07-15","ids":{"openalex":"https://openalex.org/W4385196187","doi":"https://doi.org/10.1145/3583133.3596431"},"language":"en","primary_location":{"id":"doi:10.1145/3583133.3596431","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583133.3596431","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596431","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596431","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008626424","display_name":"Pawe\u0142 Benecki","orcid":"https://orcid.org/0000-0003-4674-5393"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Pawel Benecki","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"raw_orcid":"https://orcid.org/0000-0003-4674-5393","affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057709904","display_name":"Daniel Kostrzewa","orcid":"https://orcid.org/0000-0003-2781-3709"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Daniel Kostrzewa","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"raw_orcid":"https://orcid.org/0000-0003-2781-3709","affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011490207","display_name":"Piotr Grzesik","orcid":"https://orcid.org/0000-0001-8868-0765"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Piotr Grzesik","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"raw_orcid":"https://orcid.org/0000-0001-8868-0765","affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088763621","display_name":"Bohdan Shubyn","orcid":"https://orcid.org/0000-0002-3051-1544"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Bohdan Shubyn","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"raw_orcid":"https://orcid.org/0000-0002-3051-1544","affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004555174","display_name":"Dariusz Mrozek","orcid":"https://orcid.org/0000-0001-6764-6656"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Dariusz Mrozek","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"raw_orcid":"https://orcid.org/0000-0001-6764-6656","affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I119004910"],"apc_list":null,"apc_paid":null,"fwci":0.4602,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70781155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"51","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T14319","display_name":"Currency Recognition and Detection","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9779999852180481,"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"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.762782096862793},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6799781918525696},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6493326425552368},{"id":"https://openalex.org/keywords/telemetry","display_name":"Telemetry","score":0.5866801142692566},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4722537398338318},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4372815787792206},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4224252998828888},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.41085392236709595},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3836834728717804},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.37132471799850464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2930210828781128}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.762782096862793},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6799781918525696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6493326425552368},{"id":"https://openalex.org/C183121708","wikidata":"https://www.wikidata.org/wiki/Q209867","display_name":"Telemetry","level":2,"score":0.5866801142692566},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4722537398338318},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4372815787792206},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4224252998828888},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.41085392236709595},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3836834728717804},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37132471799850464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2930210828781128},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583133.3596431","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583133.3596431","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596431","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3583133.3596431","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583133.3596431","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583133.3596431","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385196187.pdf","grobid_xml":"https://content.openalex.org/works/W4385196187.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W3176682099","https://openalex.org/W3186792524","https://openalex.org/W4280536982","https://openalex.org/W4309679176"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W2070863773","https://openalex.org/W4212896802","https://openalex.org/W2056771637","https://openalex.org/W748047311","https://openalex.org/W2359918844","https://openalex.org/W3176564347","https://openalex.org/W4298110012","https://openalex.org/W1985458517","https://openalex.org/W1612029326"],"abstract_inverted_index":{"Automated":[0],"Guided":[1],"Vehicles":[2],"(AGVs)":[3],"are":[4],"common":[5],"elements":[6],"of":[7,16,29,103,108,129,140],"contemporary":[8],"industry.":[9],"Their":[10],"continuous":[11],"operation,":[12],"and":[13,155],"thus":[14],"detection":[15,42],"anomalies":[17],"in":[18,39,120,132,158],"their":[19],"operational":[20,153],"cycles,":[21],"is":[22,37],"critical":[23],"for":[24,68,95],"uninterrupted":[25],"production":[26],"flow.":[27],"Prediction":[28],"signals,":[30],"such":[31],"as":[32],"momentary":[33],"power":[34],"consumption":[35],"(MPC),":[36],"used":[38,81],"most":[40,91],"anomaly":[41],"methods.":[43],"Feature":[44],"engineering":[45,134],"-":[46,50],"selection":[47],"or":[48],"weighting":[49,93],"can":[51,149],"significantly":[52],"improve":[53],"prediction":[54,121],"quality.":[55],"In":[56],"this":[57],"work,":[58],"we":[59],"use":[60],"a":[61,117],"genetic":[62],"algorithm":[63],"(GA)":[64],"to":[65,82,112,124,136,151],"optimize":[66],"weights":[67],"features":[69],"from":[70],"AGV":[71,146],"telemetry.":[72],"A":[73],"2-layer":[74],"Long":[75],"Short-Term":[76],"Memory":[77],"(LSTM)":[78],"network":[79],"was":[80,88,110],"predict":[83],"MPC.":[84],"Our":[85,127],"primary":[86],"goal":[87],"identifying":[89],"the":[90,125,137],"effective":[92],"strategy":[94],"enhancing":[96],"predictive":[97],"accuracy.":[98],"We":[99],"examined":[100],"different":[101],"schemes":[102],"population":[104],"initialization.":[105],"The":[106],"performance":[107],"each":[109],"compared":[111,123],"baseline":[113],"models.":[114],"Results":[115],"show":[116],"significant":[118],"improvement":[119],"quality":[122],"baseline.":[126],"application":[128],"GA":[130],"optimization":[131],"feature":[133],"contributes":[135],"growing":[138],"body":[139],"knowledge":[141],"on":[142],"developing":[143],"more":[144],"reliable":[145],"systems,":[147],"which":[148],"lead":[150],"reduced":[152],"costs":[154],"enhanced":[156],"sustainability":[157],"various":[159],"industrial":[160],"settings.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2025-10-10T00:00:00"}