{"id":"https://openalex.org/W2150143019","doi":"https://doi.org/10.1109/fuzzy.2009.5277240","title":"Dynamic system identification using recurrent neural network with multi-valued connection weight","display_name":"Dynamic system identification using recurrent neural network with multi-valued connection weight","publication_year":2009,"publication_date":"2009-08-01","ids":{"openalex":"https://openalex.org/W2150143019","doi":"https://doi.org/10.1109/fuzzy.2009.5277240","mag":"2150143019"},"language":"en","primary_location":{"id":"doi:10.1109/fuzzy.2009.5277240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2009.5277240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Fuzzy Systems","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/A5013367751","display_name":"Arit Thammano","orcid":"https://orcid.org/0000-0002-4317-7370"},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Arit Thammano","raw_affiliation_strings":["Faculty of Information Technology, King Mongkut''s Institute of Technology Ladkrabang, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, King Mongkut''s Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010451755","display_name":"Phongthep Ruxpakawong","orcid":null},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Phongthep Ruxpakawong","raw_affiliation_strings":["Faculty of Information Technology, King Mongkut''s Institute of Technology Ladkrabang, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, King Mongkut''s Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013367751"],"corresponding_institution_ids":["https://openalex.org/I91538806"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.13954773,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2077","last_page":"2082"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9861000180244446,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7982683181762695},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.7882064580917358},{"id":"https://openalex.org/keywords/connection","display_name":"Connection (principal bundle)","score":0.7711822986602783},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.7456863522529602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7284082174301147},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.690544843673706},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5593565702438354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5409266948699951},{"id":"https://openalex.org/keywords/types-of-artificial-neural-networks","display_name":"Types of artificial neural networks","score":0.5002179145812988},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.4775163233280182},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.42012742161750793},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4191700220108032},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36063241958618164},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1452164351940155}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7982683181762695},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.7882064580917358},{"id":"https://openalex.org/C13355873","wikidata":"https://www.wikidata.org/wiki/Q2920850","display_name":"Connection (principal bundle)","level":2,"score":0.7711822986602783},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.7456863522529602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7284082174301147},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.690544843673706},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5593565702438354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5409266948699951},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.5002179145812988},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.4775163233280182},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.42012742161750793},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4191700220108032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36063241958618164},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1452164351940155},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzzy.2009.5277240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2009.5277240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Fuzzy Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1958445530","https://openalex.org/W1959983357","https://openalex.org/W2029807239","https://openalex.org/W2099790451","https://openalex.org/W2110485445","https://openalex.org/W2121232771","https://openalex.org/W2155589976","https://openalex.org/W2165208076","https://openalex.org/W3133056632","https://openalex.org/W4254816979","https://openalex.org/W6641231757"],"related_works":["https://openalex.org/W2524120878","https://openalex.org/W2890297197","https://openalex.org/W2373874059","https://openalex.org/W4385254110","https://openalex.org/W2109916967","https://openalex.org/W1889674915","https://openalex.org/W1538606284","https://openalex.org/W3206636855","https://openalex.org/W2101697354","https://openalex.org/W1538193578"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3],"new":[4],"concept":[5],"of":[6,23,32,45,54],"the":[7,11,24,28,33,40,43,52,55,68],"connection":[8,47],"weight":[9,44],"to":[10,66],"standard":[12],"recurrent":[13,35],"neural":[14,36],"networks":[15,26,42,73],"-":[16],"Elman":[17],"and":[18],"Jordan":[19],"networks.":[20,37],"The":[21,59,71,81],"architecture":[22],"modified":[25,41,65,72],"is":[27,48,63],"same":[29],"as":[30],"that":[31],"original":[34,79],"However,":[38],"in":[39],"each":[46],"multi-valued,":[49],"depending":[50],"on":[51,83],"value":[53],"input":[56],"data":[57],"involved.":[58],"backpropagation":[60],"learning":[61],"algorithm":[62],"also":[64],"suit":[67],"proposed":[69],"concept.":[70],"have":[74],"been":[75],"benchmarked":[76],"against":[77],"their":[78],"counterparts.":[80],"results":[82],"eleven":[84],"benchmark":[85],"problems":[86],"are":[87],"very":[88],"encouraging.":[89]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
