{"id":"https://openalex.org/W2999989645","doi":"https://doi.org/10.1109/icmlc48188.2019.8949234","title":"A Study on Electric Scooters for the Elderly by Applying Fuzzy Theory","display_name":"A Study on Electric Scooters for the Elderly by Applying Fuzzy Theory","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2999989645","doi":"https://doi.org/10.1109/icmlc48188.2019.8949234","mag":"2999989645"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc48188.2019.8949234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc48188.2019.8949234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Machine Learning and Cybernetics (ICMLC)","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/A5090801476","display_name":"Chun-Wang Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I75357094","display_name":"National Yunlin University of Science and Technology","ror":"https://ror.org/04qkq2m54","country_code":"TW","type":"education","lineage":["https://openalex.org/I75357094"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chun-Wang Lee","raw_affiliation_strings":["Graduate School of Technological and Vocational Education, Yunlin University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Technological and Vocational Education, Yunlin University of Science and Technology","institution_ids":["https://openalex.org/I75357094"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5090801476"],"corresponding_institution_ids":["https://openalex.org/I75357094"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30451493,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14504","display_name":"Diverse Academic Research Analysis","score":0.15240000188350677,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T14504","display_name":"Diverse Academic Research Analysis","score":0.15240000188350677,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12207","display_name":"Assistive Technology in Communication and Mobility","score":0.12790000438690186,"subfield":{"id":"https://openalex.org/subfields/3609","display_name":"Occupational Therapy"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13729","display_name":"Korean Urban and Social Studies","score":0.0649000033736229,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/smoothness","display_name":"Smoothness","score":0.7995867729187012},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.677685022354126},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5710192322731018},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5669618844985962},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.5445478558540344},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.527905285358429},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4700181782245636},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44427207112312317},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.3532159626483917},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.34778302907943726},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.338787317276001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2619372606277466},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17976710200309753}],"concepts":[{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.7995867729187012},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.677685022354126},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5710192322731018},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5669618844985962},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.5445478558540344},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.527905285358429},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4700181782245636},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44427207112312317},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3532159626483917},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.34778302907943726},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.338787317276001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2619372606277466},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17976710200309753},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc48188.2019.8949234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc48188.2019.8949234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Machine Learning and Cybernetics (ICMLC)","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":10,"referenced_works":["https://openalex.org/W331197271","https://openalex.org/W1940272964","https://openalex.org/W1967169403","https://openalex.org/W2028296647","https://openalex.org/W2121035759","https://openalex.org/W2158762687","https://openalex.org/W2602436572","https://openalex.org/W2605167499","https://openalex.org/W2808067588","https://openalex.org/W2808506597"],"related_works":["https://openalex.org/W2393022482","https://openalex.org/W2377346130","https://openalex.org/W2361092061","https://openalex.org/W2319775965","https://openalex.org/W2357314690","https://openalex.org/W2191886813","https://openalex.org/W1986317414","https://openalex.org/W2163394011","https://openalex.org/W2795976185","https://openalex.org/W2353606679"],"abstract_inverted_index":{"This":[0,126],"research":[1],"is":[2],"based":[3,87],"on":[4,88,138],"fuzzy":[5,11,76,109],"comprehensive":[6],"evaluation,":[7],"and":[8,63,79,101],"lists":[9],"the":[10,26,34,44,48,52,56,65,82,89,96,103,117,124,130,134,139],"rule":[12],"table":[13],"for":[14,33,55,123],"designers":[15],"to":[16,22,42,115],"control":[17],"a":[18],"scooter,":[19],"in":[20,25,50,69],"order":[21],"affect":[23],"smoothness":[24],"product":[27],"design":[28,119],"process":[29],"of":[30,98,120,141],"electric":[31,53,70,121],"scooters":[32,122],"elderly.":[35,57,125],"Step":[36,58,73,92,106],"1:":[37],"Use":[38],"questionnaire":[39],"survey":[40],"method":[41,114],"understand":[43],"factors":[45,100,142],"considered":[46],"by":[47],"designer":[49],"designing":[51],"scooter":[54,71],"2:":[59],"Establish":[60,75],"hierarchical":[61,77],"analysis":[62],"consider":[64,95],"factor":[66],"weight":[67],"set":[68,140],"design.":[72],"3:":[74],"analysis,":[78],"sum":[80],"up":[81],"evaluation":[83],"result":[84],"set,":[85],"as":[86,111],"designer's":[90],"experience.":[91],"4:":[93],"Comprehensively":[94],"influence":[97,136],"all":[99],"obtain":[102],"judgment":[104],"result.":[105],"5:":[107],"List":[108],"rules":[110],"an":[112],"application":[113],"improve":[116],"traditional":[118],"study":[127],"found":[128],"that":[129],"travel":[131],"speed":[132],"showed":[133],"greatest":[135],"24.98%":[137],"affecting":[143],"smoothness.":[144]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}