{"id":"https://openalex.org/W2036963452","doi":"https://doi.org/10.1109/candar.2013.45","title":"Regression Analysis Using Modular Structured Neural Network","display_name":"Regression Analysis Using Modular Structured Neural Network","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2036963452","doi":"https://doi.org/10.1109/candar.2013.45","mag":"2036963452"},"language":"en","primary_location":{"id":"doi:10.1109/candar.2013.45","is_oa":false,"landing_page_url":"https://doi.org/10.1109/candar.2013.45","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 First International Symposium on Computing and Networking","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/A5103226345","display_name":"Yasuo Mitani","orcid":"https://orcid.org/0000-0002-6200-1493"},"institutions":[{"id":"https://openalex.org/I59914567","display_name":"Fukuyama City University","ror":"https://ror.org/02ms60710","country_code":"JP","type":"education","lineage":["https://openalex.org/I59914567"]},{"id":"https://openalex.org/I41661162","display_name":"Fukuyama University","ror":"https://ror.org/00mrjbj15","country_code":"JP","type":"education","lineage":["https://openalex.org/I41661162"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yasuo Mitani","raw_affiliation_strings":["Department of Electronic and Robot Engineering, Fukuyama University, Fukuyama City, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electronic and Robot Engineering, Fukuyama University, Fukuyama City, Japan","institution_ids":["https://openalex.org/I59914567","https://openalex.org/I41661162"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103226345"],"corresponding_institution_ids":["https://openalex.org/I41661162","https://openalex.org/I59914567"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.08254921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"257","last_page":"262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.986299991607666,"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/T10320","display_name":"Neural Networks and Applications","score":0.986299991607666,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9642000198364258,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T12537","display_name":"Flow Measurement and Analysis","score":0.9581000208854675,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.7881146669387817},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.7567497491836548},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6919906735420227},{"id":"https://openalex.org/keywords/stochastic-neural-network","display_name":"Stochastic neural network","score":0.6769397258758545},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5289967656135559},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5044077634811401},{"id":"https://openalex.org/keywords/modular-neural-network","display_name":"Modular neural network","score":0.49831199645996094},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4973340332508087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48538172245025635},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.43029090762138367},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4183109700679779},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38345009088516235},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.3755514919757843},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12987056374549866},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0872620940208435}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7881146669387817},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.7567497491836548},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6919906735420227},{"id":"https://openalex.org/C86582703","wikidata":"https://www.wikidata.org/wiki/Q7617824","display_name":"Stochastic neural network","level":4,"score":0.6769397258758545},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5289967656135559},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5044077634811401},{"id":"https://openalex.org/C2781121602","wikidata":"https://www.wikidata.org/wiki/Q3504403","display_name":"Modular neural network","level":4,"score":0.49831199645996094},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4973340332508087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48538172245025635},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.43029090762138367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4183109700679779},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38345009088516235},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.3755514919757843},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12987056374549866},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0872620940208435},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/candar.2013.45","is_oa":false,"landing_page_url":"https://doi.org/10.1109/candar.2013.45","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 First International Symposium on Computing and Networking","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W612593197","https://openalex.org/W1582290234","https://openalex.org/W1992592067","https://openalex.org/W2095547201","https://openalex.org/W2802033508","https://openalex.org/W4232093537","https://openalex.org/W4243323080","https://openalex.org/W4300402905","https://openalex.org/W4300945981"],"related_works":["https://openalex.org/W1558201422","https://openalex.org/W2281615551","https://openalex.org/W2317332738","https://openalex.org/W2022575851","https://openalex.org/W2367028704","https://openalex.org/W794512309","https://openalex.org/W1595652908","https://openalex.org/W2366331576","https://openalex.org/W3202211871","https://openalex.org/W3011163836"],"abstract_inverted_index":{"Paying":[0],"attention":[1],"to":[2,107],"realistic":[3],"systems":[4,16,19,36],"in":[5,74,89],"the":[6,56,66,84,90,98,108],"actual":[7,111],"engineering":[8],"fields,":[9],"we":[10],"must":[11],"very":[12],"often":[13],"treat":[14],"their":[15],"as":[17],"stochastic":[18,35],"with":[20],"non-Gaussian,":[21],"nonlinear":[22],"and/or":[23],"non-stationary":[24],"properties.":[25],"In":[26],"this":[27],"paper,":[28],"a":[29,42,80],"regression":[30,67],"analysis":[31],"method":[32,100],"for":[33,64,83],"such":[34],"is":[37,53,101],"proposed":[38,48,99],"by":[39,55,104],"introducing":[40],"reasonably":[41],"modular":[43,49],"structured":[44,50],"neural":[45,51,62,81,93],"network.":[46,94],"The":[47,95],"network":[52,63,82],"constructed":[54],"hierarchical":[57],"combination":[58],"of":[59,86,97],"each":[60,75],"expert":[61,92],"analyzing":[65],"relationship":[68],"between":[69],"input":[70],"and":[71,79,110],"output":[72],"signals":[73],"local":[76],"stationary":[77],"section,":[78],"prediction":[85],"weights":[87],"contained":[88],"above":[91],"effectiveness":[96],"experimentally":[102],"confirmed":[103],"applying":[105],"it":[106],"simulation":[109],"road":[112],"traffic":[113],"noise":[114],"data.":[115]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}