{"id":"https://openalex.org/W2097757632","doi":"https://doi.org/10.1142/s1793536914500095","title":"A MULTIPLE CLASSIFIER SYSTEM FOR PREDICTING WITH MISSING SENSOR VALUES","display_name":"A MULTIPLE CLASSIFIER SYSTEM FOR PREDICTING WITH MISSING SENSOR VALUES","publication_year":2014,"publication_date":"2014-04-01","ids":{"openalex":"https://openalex.org/W2097757632","doi":"https://doi.org/10.1142/s1793536914500095","mag":"2097757632"},"language":"en","primary_location":{"id":"doi:10.1142/s1793536914500095","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793536914500095","pdf_url":null,"source":{"id":"https://openalex.org/S16439242","display_name":"Advances in Adaptive Data Analysis","issn_l":"1793-5369","issn":["1793-5369","1793-7175"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Adaptive Data Analysis","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/A5000151716","display_name":"Ashfaqur Rahman","orcid":"https://orcid.org/0000-0002-0236-5447"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"ASHFAQUR RAHMAN","raw_affiliation_strings":["Intelligent Sensing and Systems Laboratory and Food Future Flagship, CSIRO, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Sensing and Systems Laboratory and Food Future Flagship, CSIRO, Australia","institution_ids":["https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040589907","display_name":"Qianyu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"QIANYU ZHANG","raw_affiliation_strings":["Intelligent Sensing and Systems Laboratory and Food Future Flagship, CSIRO, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Sensing and Systems Laboratory and Food Future Flagship, CSIRO, Australia","institution_ids":["https://openalex.org/I1292875679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064885417","display_name":"Claire D\u2019Este","orcid":null},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"CLAIRE D'ESTE","raw_affiliation_strings":["Intelligent Sensing and Systems Laboratory and Food Future Flagship, CSIRO, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Sensing and Systems Laboratory and Food Future Flagship, CSIRO, Australia","institution_ids":["https://openalex.org/I1292875679"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000151716"],"corresponding_institution_ids":["https://openalex.org/I1292875679"],"apc_list":null,"apc_paid":null,"fwci":0.4228,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75886644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"06","issue":"02n03","first_page":"1450009","last_page":"1450009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9947999715805054,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9947999715805054,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9908000230789185,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9839000105857849,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7769376039505005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6485702395439148},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6304411888122559},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5752149820327759},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5109571814537048},{"id":"https://openalex.org/keywords/margin-classifier","display_name":"Margin classifier","score":0.45102354884147644},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.44177180528640747},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4397071897983551},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4365488588809967},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4343966245651245},{"id":"https://openalex.org/keywords/quadratic-classifier","display_name":"Quadratic classifier","score":0.41038978099823}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7769376039505005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6485702395439148},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6304411888122559},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5752149820327759},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5109571814537048},{"id":"https://openalex.org/C173102733","wikidata":"https://www.wikidata.org/wiki/Q6760396","display_name":"Margin classifier","level":3,"score":0.45102354884147644},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.44177180528640747},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4397071897983551},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4365488588809967},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4343966245651245},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.41038978099823},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1793536914500095","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793536914500095","pdf_url":null,"source":{"id":"https://openalex.org/S16439242","display_name":"Advances in Adaptive Data Analysis","issn_l":"1793-5369","issn":["1793-5369","1793-7175"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Adaptive Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W3153808","https://openalex.org/W1484010841","https://openalex.org/W1517835688","https://openalex.org/W1817561967","https://openalex.org/W1981964712","https://openalex.org/W1988176704","https://openalex.org/W1992329416","https://openalex.org/W2032594557","https://openalex.org/W2033644761","https://openalex.org/W2044758663","https://openalex.org/W2059619857","https://openalex.org/W2076691743","https://openalex.org/W2093717447","https://openalex.org/W2096863518","https://openalex.org/W2108675631","https://openalex.org/W2122111042","https://openalex.org/W2125291718","https://openalex.org/W2128215982","https://openalex.org/W2133990480","https://openalex.org/W2134699177","https://openalex.org/W2147564534","https://openalex.org/W2149706766","https://openalex.org/W2326945647","https://openalex.org/W2912934387","https://openalex.org/W3004732066","https://openalex.org/W3120740533","https://openalex.org/W4212883601","https://openalex.org/W4236137412"],"related_works":["https://openalex.org/W2162083125","https://openalex.org/W1483596504","https://openalex.org/W2009506202","https://openalex.org/W58702947","https://openalex.org/W47559851","https://openalex.org/W2297694731","https://openalex.org/W204488290","https://openalex.org/W2096969571","https://openalex.org/W2040550925","https://openalex.org/W2112112609"],"abstract_inverted_index":{"Sensors":[0],"placed":[1],"in":[2,65],"the":[3,66,89,100,104,116,127,134,141,148,151,167],"field":[4],"frequently":[5],"suffer":[6],"faults":[7],"or":[8],"communication":[9],"errors,":[10],"causing":[11],"readings":[12],"to":[13,24,29,98],"become":[14],"unavailable":[15],"for":[16,40,79,118],"prediction":[17,135,144],"purposes.":[18],"Statistical":[19],"approaches":[20,158],"are":[21],"commonly":[22],"used":[23],"generate":[25],"an":[26],"artificial":[27,58],"value":[28],"approximate":[30],"a":[31,37,47,76,93,108,161],"missing":[32,61,130],"sensor":[33],"reading":[34],"and":[35,106,137,143,159],"complete":[36],"feature":[38,72],"vector":[39],"prediction.":[41],"In":[42],"this":[43,119],"paper,":[44],"we":[45,124],"present":[46],"new":[48],"multiple":[49,153],"classifier":[50,64,77,154],"system":[51,67,155],"that":[52,75,114],"is":[53,68],"capable":[54],"of":[55,60,83,95,103,129,150],"predicting":[56],"without":[57],"approximations":[59],"values.":[62],"Each":[63],"trained":[69],"on":[70,92,107,163],"different":[71],"subsets,":[73],"so":[74],"exists":[78],"each":[80],"potential":[81],"combination":[82],"available":[84],"features.":[85],"We":[86,146],"have":[87],"evaluated":[88],"proposed":[90,152],"approach":[91],"set":[94],"benchmark":[96,122],"datasets":[97],"establish":[99],"generic":[101],"nature":[102],"problem,":[105],"real-world":[109],"environmental":[110],"event":[111],"detection":[112],"application":[113],"inspires":[115],"need":[117],"work.":[120],"On":[121],"datasets,":[123],"artificially":[125],"vary":[126],"percentage":[128],"values":[131],"(i)":[132],"during":[133,139],"phase,":[136],"(ii)":[138],"both":[140],"training":[142],"phases.":[145],"compare":[147],"performance":[149],"against":[156],"statistical":[157],"provide":[160],"guideline":[162],"their":[164],"suitability":[165],"under":[166],"above":[168],"scenarios.":[169]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}