{"id":"https://openalex.org/W2748639800","doi":"https://doi.org/10.1109/fuzz-ieee.2017.8015723","title":"A new learning approach for Takagi-Sugeno fuzzy systems applied to time series prediction","display_name":"A new learning approach for Takagi-Sugeno fuzzy systems applied to time series prediction","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2748639800","doi":"https://doi.org/10.1109/fuzz-ieee.2017.8015723","mag":"2748639800"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2017.8015723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2017.8015723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5076866574","display_name":"Rosa Altilio","orcid":null},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Rosa Altilio","raw_affiliation_strings":["Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \u201cLa Sapienza\u201d, Rome, Italy","Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \"La Sapienza\", Rome, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \u201cLa Sapienza\u201d, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \"La Sapienza\", Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052397999","display_name":"Antonello Rosato","orcid":"https://orcid.org/0000-0002-4371-5925"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Antonello Rosato","raw_affiliation_strings":["Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \u201cLa Sapienza\u201d, Rome, Italy","Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \"La Sapienza\", Rome, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \u201cLa Sapienza\u201d, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \"La Sapienza\", Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015796693","display_name":"Massimo Panella","orcid":"https://orcid.org/0000-0002-9876-1494"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Massimo Panella","raw_affiliation_strings":["Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \u201cLa Sapienza\u201d, Rome, Italy","Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \"La Sapienza\", Rome, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \u201cLa Sapienza\u201d, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Department of Information Engineering Electronics and Telecommunications (DIET), University of Rome \"La Sapienza\", Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076866574"],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":null,"apc_paid":null,"fwci":0.39,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.70404329,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"23","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9987999796867371,"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":0.9987999796867371,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9987000226974487,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6527031064033508},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6520053744316101},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6401649713516235},{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.6214222311973572},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6117159128189087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5852231383323669},{"id":"https://openalex.org/keywords/neuro-fuzzy","display_name":"Neuro-fuzzy","score":0.5798860788345337},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5510851740837097},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5267999768257141},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5148524641990662},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.47299012541770935},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.448773056268692},{"id":"https://openalex.org/keywords/fuzzy-inference","display_name":"Fuzzy inference","score":0.4258075952529907},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4163970649242401},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32966458797454834}],"concepts":[{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6527031064033508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6520053744316101},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6401649713516235},{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.6214222311973572},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6117159128189087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5852231383323669},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.5798860788345337},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5510851740837097},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5267999768257141},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5148524641990662},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.47299012541770935},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.448773056268692},{"id":"https://openalex.org/C2986395286","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy inference","level":5,"score":0.4258075952529907},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4163970649242401},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32966458797454834},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fuzz-ieee.2017.8015723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2017.8015723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.uniroma1.it:11573/987109","is_oa":false,"landing_page_url":"http://ieeexplore.ieee.org/document/8015723/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1528056948","https://openalex.org/W1570834090","https://openalex.org/W1586335931","https://openalex.org/W1988518729","https://openalex.org/W1996619812","https://openalex.org/W2019207321","https://openalex.org/W2053794432","https://openalex.org/W2062897401","https://openalex.org/W2065802302","https://openalex.org/W2066145652","https://openalex.org/W2068844879","https://openalex.org/W2096930863","https://openalex.org/W2100330461","https://openalex.org/W2103414828","https://openalex.org/W2109649072","https://openalex.org/W2111440106","https://openalex.org/W2124776405","https://openalex.org/W2137820384","https://openalex.org/W2146552111","https://openalex.org/W2152161790","https://openalex.org/W2156683472","https://openalex.org/W2161940528","https://openalex.org/W2162459787","https://openalex.org/W2162635690","https://openalex.org/W2168530688","https://openalex.org/W2557279148","https://openalex.org/W4210509282"],"related_works":["https://openalex.org/W2785395359","https://openalex.org/W1549951490","https://openalex.org/W2247295643","https://openalex.org/W2111426611","https://openalex.org/W1966629635","https://openalex.org/W3159983598","https://openalex.org/W2357953609","https://openalex.org/W2367175432","https://openalex.org/W2374727787","https://openalex.org/W2288384671"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,94],"study":[6],"on":[7],"the":[8,18,28,43,86,89,98],"use":[9],"of":[10,20,27,45,88,97],"fuzzy":[11,38,48,74],"neural":[12,72,75],"networks":[13],"and":[14,73],"their":[15],"application":[16],"to":[17,36,70,84],"prediction":[19,96],"times":[21],"series":[22],"generated":[23],"by":[24],"complex":[25],"processes":[26],"real-world.":[29],"The":[30,50,66],"new":[31],"learning":[32],"strategy":[33],"is":[34,82],"suited":[35],"any":[37],"inference":[39],"model,":[40],"especially":[41],"in":[42],"case":[44],"higher-order":[46],"Sugeno-type":[47],"rules.":[49],"data":[51],"considered":[52],"herein":[53],"are":[54],"real-world":[55],"cases":[56],"concerning":[57],"chaotic":[58],"benchmarks":[59],"as":[60,62],"well":[61],"environmental":[63],"time":[64,100],"series.":[65,101],"comparison":[67],"with":[68,93],"respect":[69],"well-known":[71],"models":[76],"will":[77],"prove":[78],"that":[79],"our":[80],"approach":[81],"able":[83],"follow":[85],"behavior":[87],"underlying,":[90],"unknown":[91],"process":[92],"good":[95],"observed":[99]},"counts_by_year":[{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
