{"id":"https://openalex.org/W4281857401","doi":"https://doi.org/10.1145/3523286.3524569","title":"A new fusion model for anomaly detection of gas data","display_name":"A new fusion model for anomaly detection of gas data","publication_year":2022,"publication_date":"2022-01-21","ids":{"openalex":"https://openalex.org/W4281857401","doi":"https://doi.org/10.1145/3523286.3524569"},"language":"en","primary_location":{"id":"doi:10.1145/3523286.3524569","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523286.3524569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","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/A5065510117","display_name":"DongHong Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"DongHong Huang","raw_affiliation_strings":["BEIJING GAS GROUP CO., LTO., China"],"affiliations":[{"raw_affiliation_string":"BEIJING GAS GROUP CO., LTO., China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326831","display_name":"Dan Liu","orcid":"https://orcid.org/0000-0002-2198-3910"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan Liu","raw_affiliation_strings":["BEIJING GAS GROUP CO., LTO., China"],"affiliations":[{"raw_affiliation_string":"BEIJING GAS GROUP CO., LTO., China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009730378","display_name":"Ming Wen","orcid":"https://orcid.org/0000-0001-7103-0192"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Wen","raw_affiliation_strings":["BEIJING GAS GROUP CO., LTO., China"],"affiliations":[{"raw_affiliation_string":"BEIJING GAS GROUP CO., LTO., China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065510117"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04701061,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"357","last_page":"361"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10876","display_name":"Fault Detection and Control Systems","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9448999762535095,"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/computer-science","display_name":"Computer science","score":0.645403265953064},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6110959649085999},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5815560817718506},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5419328212738037},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.48034894466400146},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.4721051752567291},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4706886112689972},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.45951998233795166},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4284265339374542},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.4210216999053955},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37913501262664795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26786088943481445},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1498473584651947},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07677623629570007}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.645403265953064},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6110959649085999},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5815560817718506},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5419328212738037},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.48034894466400146},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.4721051752567291},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4706886112689972},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.45951998233795166},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4284265339374542},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4210216999053955},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37913501262664795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26786088943481445},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1498473584651947},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07677623629570007},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3523286.3524569","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523286.3524569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2521519254","https://openalex.org/W3139833644","https://openalex.org/W3123110765","https://openalex.org/W4399531511","https://openalex.org/W3081133439","https://openalex.org/W4386246791","https://openalex.org/W2945537679","https://openalex.org/W3211701140","https://openalex.org/W2952280724","https://openalex.org/W2133103607"],"abstract_inverted_index":{"Accurate":[0],"gas":[1,10,23,37,90,131],"data":[2,24,91,107,132],"are":[3],"needed":[4],"to":[5,30,71,100,104],"support":[6],"the":[7,16,32,45,65,73,77,106,110,114,118,123],"construction":[8],"of":[9,36,49,76,89,120],"energy":[11],"consumption":[12],"monitoring":[13],"system.":[14],"In":[15,28],"sampling":[17,94],"process,":[18],"we":[19],"found":[20],"that":[21,113],"some":[22],"had":[25],"certain":[26],"errors.":[27],"order":[29],"improve":[31,105],"accuracy":[33,119],"and":[34,43,47,57,126],"reliability":[35],"data,":[38],"this":[39,98],"paper":[40],"deeply":[41],"studied":[42],"analyzed":[44],"advantages":[46],"disadvantages":[48],"four":[50,67,78],"algorithm":[51,61,116],"models,":[52],"k-means,":[53],"LOF,":[54],"isolated":[55],"forest":[56],"One-Class":[58],"SVM.A":[59],"fusion":[60,115],"model":[62,99],"based":[63],"on":[64,86],"above":[66],"models":[68],"is":[69,83],"proposed":[70],"realize":[72],"multi-dimensional":[74],"complementarity":[75],"basic":[79],"models.":[80],"Anomaly":[81],"detection":[82],"carried":[84],"out":[85],"two":[87,93],"groups":[88],"at":[92],"points":[95,103],"by":[96],"using":[97],"find":[101],"abnormal":[102],"quality.":[108],"Finally,":[109],"experiment":[111],"proves":[112],"improves":[117],"detection,":[121],"saves":[122],"running":[124],"time,":[125],"achieves":[127],"satisfactory":[128],"results":[129],"in":[130],"processing.":[133]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
