{"id":"https://openalex.org/W4416677060","doi":"https://doi.org/10.1109/dsaa65442.2025.11248032","title":"A Comparative Study of Non-Linear Modelling Capabilities of T-S Fuzzy Models and Back-Propagation Neural Networks","display_name":"A Comparative Study of Non-Linear Modelling Capabilities of T-S Fuzzy Models and Back-Propagation Neural Networks","publication_year":2025,"publication_date":"2025-10-09","ids":{"openalex":"https://openalex.org/W4416677060","doi":"https://doi.org/10.1109/dsaa65442.2025.11248032"},"language":null,"primary_location":{"id":"doi:10.1109/dsaa65442.2025.11248032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11248032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","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/A5068995921","display_name":"Linxiang Li","orcid":"https://orcid.org/0000-0002-3409-6608"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linxiang Li","raw_affiliation_strings":["Harbin Institute of Technology,Center for Control Theory and Guidance Technology,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Center for Control Theory and Guidance Technology,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016104023","display_name":"Kainan Liu","orcid":"https://orcid.org/0009-0005-6005-3619"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kainan Liu","raw_affiliation_strings":["Harbin Institute of Technology,Center for Control Theory and Guidance Technology,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Center for Control Theory and Guidance Technology,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104053509","display_name":"Xiaojun Ban","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Ban","raw_affiliation_strings":["Harbin Institute of Technology,Center for Control Theory and Guidance Technology,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Center for Control Theory and Guidance Technology,Harbin,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088011162","display_name":"Shengkun Xie","orcid":"https://orcid.org/0000-0002-9533-2096"},"institutions":[{"id":"https://openalex.org/I4210091032","display_name":"Ted Rogers Centre for Heart Research","ror":"https://ror.org/00cgnj660","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I1325899441","https://openalex.org/I185261750","https://openalex.org/I4210091032","https://openalex.org/I4210141030"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Shengkun Xie","raw_affiliation_strings":["Toronto Metropolitan University,Ted Rogers School of Management,Toronto,Canada"],"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University,Ted Rogers School of Management,Toronto,Canada","institution_ids":["https://openalex.org/I4210091032"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068995921"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20340524,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.40799999237060547,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.40799999237060547,"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/T10320","display_name":"Neural Networks and Applications","score":0.11400000005960464,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.09730000048875809,"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/adaptability","display_name":"Adaptability","score":0.8022000193595886},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6873999834060669},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5432000160217285},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5292999744415283},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.49230000376701355},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.40779998898506165},{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.40380001068115234},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.38909998536109924},{"id":"https://openalex.org/keywords/neuro-fuzzy","display_name":"Neuro-fuzzy","score":0.3508000075817108}],"concepts":[{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.8022000193595886},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6873999834060669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6653000116348267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5877000093460083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5493999719619751},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5432000160217285},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5292999744415283},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49230000376701355},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.446399986743927},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.40779998898506165},{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.40380001068115234},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.38909998536109924},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.3508000075817108},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.3431999981403351},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32510000467300415},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa65442.2025.11248032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11248032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"}],"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/W2003967703","https://openalex.org/W2019826979","https://openalex.org/W2033796271","https://openalex.org/W2101087531","https://openalex.org/W2102641351","https://openalex.org/W2103496339","https://openalex.org/W2112796928","https://openalex.org/W2116261113","https://openalex.org/W2160327601","https://openalex.org/W2167861481","https://openalex.org/W2890706287","https://openalex.org/W2963749936","https://openalex.org/W2963847595","https://openalex.org/W2964106644","https://openalex.org/W2983075708","https://openalex.org/W4243392184","https://openalex.org/W4312735521","https://openalex.org/W4323065890","https://openalex.org/W4388426071","https://openalex.org/W4390874448","https://openalex.org/W4392939427","https://openalex.org/W4400315298","https://openalex.org/W4401413876","https://openalex.org/W4402351388","https://openalex.org/W4402352501","https://openalex.org/W4403482223","https://openalex.org/W4404813925"],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,36,116,176],"era":[2],"of":[3,59,67,91,121],"data-driven":[4],"decision-making,":[5],"selecting":[6],"appropriate":[7],"nonlinear":[8,205],"modeling":[9,62,84,100,201],"techniques":[10],"is":[11],"critical":[12],"for":[13,168,186,203],"building":[14],"robust":[15],"and":[16,26,85,87,105,119,148,195],"interpretable":[17],"predictive":[18,76,170,200],"systems.":[19,93,206],"While":[20],"both":[21],"Takagi-Sugeno":[22],"(T-S)":[23],"fuzzy":[24,130,156],"models":[25,131,157],"Back-Propagation":[27],"(BP)":[28],"neural":[29,141],"networks":[30,142],"are":[31],"well-established":[32],"universal":[33],"approximators":[34],"in":[35,75,135,151,161],"data":[37,178],"science":[38,179],"domain,":[39],"their":[40],"fundamentally":[41],"different":[42],"structural":[43],"characteristics":[44],"lead":[45],"to":[46,71,103,107,146,175,198],"varied":[47],"performance":[48,96],"across":[49,97],"application":[50],"scenarios.":[51],"This":[52,172],"paper":[53],"presents":[54],"a":[55,65,183],"systematic":[56],"comparative":[57],"study":[58,173],"these":[60],"two":[61],"approaches":[63],"through":[64],"series":[66],"simulation":[68],"experiments":[69],"designed":[70],"reflect":[72],"key":[73],"tasks":[74],"analytics,":[77],"including":[78],"static":[79],"function":[80],"approximation,":[81],"dynamic":[82,163],"system":[83],"forecasting,":[86],"real-time":[88],"state":[89],"tracking":[90],"time-varying":[92],"By":[94],"evaluating":[95],"multiple":[98],"dimensions":[99],"accuracy,":[101],"robustness":[102],"noise,":[104],"adaptability":[106,160],"temporal":[108],"dynamics,":[109],"this":[110],"work":[111],"provides":[112],"actionable":[113],"insights":[114],"into":[115],"practical":[117],"strengths":[118],"limitations":[120],"each":[122],"model":[123,187],"type.":[124],"The":[125],"results":[126],"show":[127],"that":[128],"T-S":[129,155],"offer":[132],"superior":[133],"accuracy":[134],"clean,":[136],"stable":[137],"environments,":[138],"while":[139],"BP":[140],"demonstrate":[143],"strong":[144],"resilience":[145],"noise":[147],"generalization":[149],"ability":[150],"uncertain":[152],"conditions.":[153],"Additionally,":[154],"exhibit":[158],"higher":[159],"real-time,":[162],"contexts,":[164],"making":[165],"them":[166],"valuable":[167],"time-sensitive":[169],"applications.":[171],"contributes":[174],"broader":[177],"community":[180],"by":[181],"offering":[182],"structured":[184],"framework":[185],"selection":[188],"based":[189],"on":[190],"application-specific":[191],"demands,":[192],"helping":[193],"practitioners":[194],"researchers":[196],"alike":[197],"optimize":[199],"strategies":[202],"complex,":[204]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-25T00:00:00"}
