{"id":"https://openalex.org/W3184385149","doi":"https://doi.org/10.1109/tkde.2021.3099135","title":"Composite Neural Network: Theory and Application to PM2.5 Prediction","display_name":"Composite Neural Network: Theory and Application to PM2.5 Prediction","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3184385149","doi":"https://doi.org/10.1109/tkde.2021.3099135","mag":"3184385149"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3099135","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3099135","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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/A5102413492","display_name":"Ming-Chuan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Ming-Chuan Yang","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, 38017 Taipei, Taipei, Taiwan, 115 (e-mail: mingchuan@iis.sinica.edu.tw)","Institute of Information Science, Academia Sinica, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, 38017 Taipei, Taipei, Taiwan, 115 (e-mail: mingchuan@iis.sinica.edu.tw)","institution_ids":["https://openalex.org/I4210098366"]},{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052520979","display_name":"Meng Chang Chen","orcid":"https://orcid.org/0000-0002-6815-2436"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Meng Chang Chen","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, Taipei, Taipei, Taiwan, (e-mail: mcc@iis.sinica.edu.tw)","Institute of Information Science, Academia Sinica, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Taipei, Taipei, Taiwan, (e-mail: mcc@iis.sinica.edu.tw)","institution_ids":["https://openalex.org/I4210098366"]},{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102413492"],"corresponding_institution_ids":["https://openalex.org/I4210098366"],"apc_list":null,"apc_paid":null,"fwci":0.8051,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.67982008,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10190","display_name":"Air Quality and Health Impacts","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.8067296743392944},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7237617373466492},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.635853111743927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6205540299415588},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5651829838752747},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5047999620437622},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33114996552467346},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19950059056282043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8067296743392944},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7237617373466492},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.635853111743927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6205540299415588},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5651829838752747},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5047999620437622},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33114996552467346},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19950059056282043},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2021.3099135","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3099135","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2065147761","display_name":null,"funder_award_id":"108-2221-E-001-015 and 109-2119-M-001-010-A","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1485009520","https://openalex.org/W1546509353","https://openalex.org/W1645816215","https://openalex.org/W1969865391","https://openalex.org/W1971402834","https://openalex.org/W1988115241","https://openalex.org/W1988790447","https://openalex.org/W2008056655","https://openalex.org/W2023294425","https://openalex.org/W2032576386","https://openalex.org/W2073040595","https://openalex.org/W2097415784","https://openalex.org/W2100128988","https://openalex.org/W2107386336","https://openalex.org/W2138857742","https://openalex.org/W2165698076","https://openalex.org/W2169707207","https://openalex.org/W2342750929","https://openalex.org/W2463983882","https://openalex.org/W2590019597","https://openalex.org/W2604559389","https://openalex.org/W2754102394","https://openalex.org/W2767894694","https://openalex.org/W2809035759","https://openalex.org/W2893230400","https://openalex.org/W2962739339","https://openalex.org/W2979473749","https://openalex.org/W2990955039","https://openalex.org/W2998704965","https://openalex.org/W3001108747","https://openalex.org/W3113701344","https://openalex.org/W3123329971","https://openalex.org/W3123995874","https://openalex.org/W4229706427","https://openalex.org/W4232478844","https://openalex.org/W4240294902","https://openalex.org/W4289857829","https://openalex.org/W4300792872","https://openalex.org/W6680300913","https://openalex.org/W6680532216","https://openalex.org/W6762338880","https://openalex.org/W6767101815"],"related_works":["https://openalex.org/W1667647204","https://openalex.org/W2404647514","https://openalex.org/W4247536566","https://openalex.org/W4241418540","https://openalex.org/W2018477250","https://openalex.org/W3119814709","https://openalex.org/W1508895727","https://openalex.org/W2725786787","https://openalex.org/W1590965489","https://openalex.org/W1875930651"],"abstract_inverted_index":{"This":[0],"work":[1],"investigates":[2],"the":[3,10,75,83,118,130,156,165,168,174,180],"framework":[4,131],"and":[5,22,77,82,96,136],"statistical":[6],"performance":[7,120],"guarantee":[8],"of":[9,17,20,55,79,132,147,167,177],"composite":[11,107,134,140,170,182],"neural":[12,24,40,67,108,141,183],"network,":[13,135],"which":[14],"is":[15,43,72,85],"composed":[16],"a":[18,29,50,57,61,65,102,106,115,133,139,152,160],"collection":[19],"pre-trained":[21,39,58,149],"non-instantiated":[23],"network":[25,41,68,109,142,171,184],"models":[26,185],"connected":[27],"as":[28,60,91,93],"rooted":[30],"directed":[31],"acyclic":[32],"graph,":[33],"for":[34,98],"solving":[35],"complicated":[36,66,161],"applications.":[37],"A":[38],"model":[42,59,99],"generally":[44],"well":[45,92],"trained,":[46],"targeted":[47],"to":[48],"approximate":[49],"specific":[51],"function.":[52],"The":[53],"advantages":[54],"adopting":[56],"component":[62],"in":[63,88],"composing":[64],"are":[69,122],"two-fold.":[70],"One":[71],"benefiting":[73],"from":[74],"intelligence":[76],"diligence":[78],"domain":[80],"experts,":[81],"other":[84,189],"saving":[86],"effort":[87],"data":[89],"acquisition":[90],"computing":[94],"resources":[95],"time":[97],"training.":[100],"Despite":[101],"general":[103],"belief":[104],"that":[105,138],"may":[110],"perform":[111,186],"better":[112,144,187],"than":[113,145,188],"any":[114,146],"single":[116],"component,":[117],"overall":[119],"characteristics":[121],"not":[123],"clear.":[124],"In":[125,155,173],"this":[126],"work,":[127],"we":[128,158],"propose":[129],"prove":[137],"performs":[143],"its":[148],"components":[150],"with":[151],"high":[153],"probability.":[154],"study,":[157],"explore":[159],"application---PM2.5":[162],"prediction---to":[163],"support":[164],"correctness":[166],"proposed":[169],"theory.":[172],"empirical":[175],"evaluations":[176],"PM2.5":[178],"prediction,":[179],"constructed":[181],"machine":[190],"learning":[191],"models.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
