{"id":"https://openalex.org/W2979068235","doi":"https://doi.org/10.1109/ijcnn.2019.8852364","title":"A Hybrid Incremental Regression Neural Network for Uncertain Data Streams","display_name":"A Hybrid Incremental Regression Neural Network for Uncertain Data Streams","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2979068235","doi":"https://doi.org/10.1109/ijcnn.2019.8852364","mag":"2979068235"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852364","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852364","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5062917240","display_name":"Hang Yu","orcid":"https://orcid.org/0000-0003-3444-9992"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Hang Yu","raw_affiliation_strings":["Centre for Artificial Intelligence Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100675577","display_name":"Jie L\u00fc","orcid":"https://orcid.org/0000-0003-0690-4732"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jie Lu","raw_affiliation_strings":["Centre for Artificial Intelligence Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056050667","display_name":"Jialu Xu","orcid":"https://orcid.org/0000-0002-7745-2000"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialu Xu","raw_affiliation_strings":["Centre for Wise Information Systems Faculty of Engineering and Computer Scienceline, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Centre for Wise Information Systems Faculty of Engineering and Computer Scienceline, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062192039","display_name":"Guangquan Zhang","orcid":"https://orcid.org/0000-0003-3960-0583"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guangquan Zhang","raw_affiliation_strings":["Centre for Artificial Intelligence Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5062917240"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":0.5772,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76287111,"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9991999864578247,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9991999864578247,"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/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9807000160217285,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9789000153541565,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.7490534782409668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7015852928161621},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6455435752868652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478954315185547},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5192113518714905},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.506246030330658},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4936331510543823},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4347476661205292},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1491987407207489},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12592798471450806}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7490534782409668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7015852928161621},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6455435752868652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478954315185547},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5192113518714905},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.506246030330658},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4936331510543823},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4347476661205292},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1491987407207489},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12592798471450806}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852364","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852364","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/137506","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/137506","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1521993350","https://openalex.org/W1964357740","https://openalex.org/W1997215856","https://openalex.org/W2013220899","https://openalex.org/W2013668940","https://openalex.org/W2019950953","https://openalex.org/W2045938006","https://openalex.org/W2073427650","https://openalex.org/W2098263691","https://openalex.org/W2103502816","https://openalex.org/W2120250216","https://openalex.org/W2150159007","https://openalex.org/W2150621701","https://openalex.org/W2153192561","https://openalex.org/W2156145910","https://openalex.org/W2167505604","https://openalex.org/W2609002182","https://openalex.org/W2758219826","https://openalex.org/W2783695918","https://openalex.org/W2809044420","https://openalex.org/W2809113080","https://openalex.org/W2912565176","https://openalex.org/W2952023274","https://openalex.org/W4211007335","https://openalex.org/W4230588984","https://openalex.org/W6684876124","https://openalex.org/W6737135848"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852","https://openalex.org/W2621086889"],"abstract_inverted_index":{"The":[0],"design":[1],"of":[2,24,67,74,106,133,151],"classical":[3],"regression":[4,52,85,108,124,141,153,168,177,196,206],"algorithms":[5,53,69],"was":[6],"based":[7,88],"on":[8,89,184],"the":[9,13,22,65,72,75,104,107,123,131,149,152,158],"assumption":[10],"that":[11,191],"all":[12],"required":[14],"data":[15,28,38,56,76],"is":[16,29,77,144,171],"obtained":[17,112],"at":[18],"one":[19],"time.":[20],"With":[21],"emergence":[23],"big":[25],"data,":[26],"however,":[27],"increasingly":[30],"displayed":[31],"in":[32,37,46,57],"sequence":[33],"form,":[34],"such":[35],"as":[36,130],"streams,":[39],"and":[40,94,161,187],"can":[41],"be":[42],"read":[43],"only":[44],"once":[45],"a":[47,58,82],"specific":[48],"order.":[49],"Many":[50],"incremental":[51,84,91,95,117,137,167,195,205],"which":[54],"process":[55],"sequential":[59],"manner":[60],"have":[61],"been":[62],"proposed,":[63],"but":[64],"accuracy":[66],"these":[68],"deteriorates":[70],"when":[71],"value":[73],"uncertain.":[78],"This":[79,121],"paper":[80],"proposes":[81],"hybrid":[83,166,194],"neural":[86,92,109,118,125,154,169,197],"network":[87,93,110,119,126,170,198],"self-organizing":[90],"fuzzy":[96,138],"support":[97,139],"vector":[98,140],"regression.":[99],"In":[100],"our":[101,164,192],"proposed":[102,165,193],"network,":[103],"neurons":[105,134],"are":[111],"by":[113],"an":[114,175],"improved":[115,159],"self-organized":[116],"(SOINN).":[120],"enables":[122],"structure":[127],"to":[128,147,173,203],"self-organize":[129],"number":[132],"increases.":[135],"An":[136],"(IFSVR)":[142],"algorithm":[143],"then":[145],"used":[146],"modify":[148],"parameters":[150],"network.":[155],"By":[156],"combining":[157],"SOINN":[160],"IFSVR":[162],"algorithms,":[163],"able":[172],"learn":[174],"accurate":[176],"model":[178],"from":[179],"large":[180],"uncertain":[181],"data.":[182],"Experiments":[183],"both":[185],"artificial":[186],"real-world":[188],"datasets":[189],"indicate":[190],"achieves":[199],"superior":[200],"performance":[201],"compared":[202],"other":[204],"algorithms.":[207]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}