{"id":"https://openalex.org/W7125920766","doi":"https://doi.org/10.1109/smc58881.2025.11343116","title":"Bridging Causal Discovery and Fuzzy Systems: An Efficient Rule-Based Modeling Approach","display_name":"Bridging Causal Discovery and Fuzzy Systems: An Efficient Rule-Based Modeling Approach","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125920766","doi":"https://doi.org/10.1109/smc58881.2025.11343116"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343116","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5124126812","display_name":"Yishen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yishen Li","raw_affiliation_strings":["Beijing University of Post and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Post and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124079968","display_name":"Tao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wang","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100750717","display_name":"Yuliang Li","orcid":"https://orcid.org/0000-0002-0625-3995"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuliang Li","raw_affiliation_strings":["Beijing University of Post and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Post and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124119075","display_name":"Fuchun Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchun Sun","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3677","last_page":"3684"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.49410000443458557,"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":0.49410000443458557,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.11710000038146973,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.10920000076293945,"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/interpretability","display_name":"Interpretability","score":0.9089999794960022},{"id":"https://openalex.org/keywords/markov-blanket","display_name":"Markov blanket","score":0.70660001039505},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6256999969482422},{"id":"https://openalex.org/keywords/fuzzy-rule","display_name":"Fuzzy rule","score":0.4496999979019165},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.43639999628067017},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.4311000108718872},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.37709999084472656},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.36910000443458557}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9089999794960022},{"id":"https://openalex.org/C123867240","wikidata":"https://www.wikidata.org/wiki/Q3001792","display_name":"Markov blanket","level":5,"score":0.70660001039505},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6256999969482422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5835999846458435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.541100025177002},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5080999732017517},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5047000050544739},{"id":"https://openalex.org/C2780049643","wikidata":"https://www.wikidata.org/wiki/Q5511139","display_name":"Fuzzy rule","level":4,"score":0.4496999979019165},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.4311000108718872},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.3310999870300293},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29660001397132874},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.2937000095844269},{"id":"https://openalex.org/C127385683","wikidata":"https://www.wikidata.org/wiki/Q1475696","display_name":"Fuzzy classification","level":4,"score":0.271699994802475},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C148671577","wikidata":"https://www.wikidata.org/wiki/Q5511133","display_name":"Fuzzy set operations","level":4,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343116","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":28,"referenced_works":["https://openalex.org/W1197622812","https://openalex.org/W1564250772","https://openalex.org/W1977446441","https://openalex.org/W2019207321","https://openalex.org/W2046738003","https://openalex.org/W2050288270","https://openalex.org/W2079325629","https://openalex.org/W2143891888","https://openalex.org/W2155263265","https://openalex.org/W2577227262","https://openalex.org/W2593118993","https://openalex.org/W2790171198","https://openalex.org/W2902062307","https://openalex.org/W2910646677","https://openalex.org/W2945976633","https://openalex.org/W2948579453","https://openalex.org/W2957453042","https://openalex.org/W3021933602","https://openalex.org/W3130267661","https://openalex.org/W3135588948","https://openalex.org/W4213345774","https://openalex.org/W4224013576","https://openalex.org/W4225494991","https://openalex.org/W4378527954","https://openalex.org/W4388517681","https://openalex.org/W4388867906","https://openalex.org/W4401331151","https://openalex.org/W4402401595"],"related_works":[],"abstract_inverted_index":{"Generating":[0],"fuzzy":[1,11,104,170],"rule":[2,26,44],"bases":[3],"from":[4],"data":[5],"is":[6],"essential":[7],"for":[8,172],"building":[9],"interpretable":[10,169],"systems.":[12],"Traditional":[13],"approaches":[14],"like":[15,111],"Wang-Mendel":[16],"(WM)":[17],"rely":[18],"on":[19,63],"correlations":[20],"but":[21,60],"often":[22],"produce":[23],"large,":[24],"redundant":[25],"bases,":[27],"reducing":[28],"interpretability":[29,141],"and":[30,88,114,120,127,142],"increasing":[31],"computational":[32],"cost.":[33],"To":[34],"address":[35],"this,":[36],"recent":[37],"work":[38,161],"has":[39],"incorporated":[40],"causal":[41,92,108,125,136],"discovery":[42,126],"into":[43],"generation.":[45],"Te":[46],"Zhang":[47],"et":[48],"al.":[49],"introduced":[50],"a":[51,83,101,163],"method":[52],"using":[53],"directed":[54],"graphs":[55],"within":[56],"the":[57,73,131],"Markov":[58,86],"blanket,":[59],"their":[61],"reliance":[62],"DirectLiNGAM":[64],"limits":[65],"applicability":[66],"to":[67,81,100,107,167],"linear":[68],"data.":[69,174],"This":[70,160],"paper":[71],"adopts":[72],"Causal":[74],"Additive":[75],"Model":[76],"with":[77],"Unobserved":[78],"Variables":[79],"(CAMUV)":[80],"identify":[82],"target":[84],"variable\u2019s":[85],"blanket":[87],"extract":[89],"its":[90],"direct":[91],"features.":[93],"These":[94],"are":[95],"then":[96],"used":[97],"as":[98],"inputs":[99],"Takagi-Sugeno-Kang":[102],"(TSK)":[103],"system.":[105],"Compared":[106],"learning":[109],"algorithms":[110],"GRaSP,":[112],"DECI,":[113],"BOSS,":[115],"CAMUV":[116],"better":[117],"handles":[118],"nonlinear":[119],"partially":[121],"unobserved":[122],"data,":[123],"enhancing":[124],"interpretability.":[128],"Unlike":[129],"WM,":[130],"TSK":[132],"system":[133],"generates":[134],"dynamic":[135],"if-then":[137],"rules,":[138],"improving":[139],"both":[140],"modeling":[143],"power.":[144],"Experiments":[145],"across":[146],"seven":[147],"datasets":[148],"show":[149],"an":[150],"average":[151],"accuracy":[152],"improvement":[153],"of":[154],"approximately":[155],"5%":[156],"over":[157],"benchmark":[158],"models.":[159],"offers":[162],"novel,":[164],"causality-driven":[165],"approach":[166],"constructing":[168],"systems":[171],"complex":[173]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-29T00:00:00"}
