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dc.contributor.authorLin, Yu-Chengen_US
dc.contributor.authorWang, Yu-Chengen_US
dc.contributor.authorChen, Tin-Chih Tolyen_US
dc.contributor.authorLin, Hai-Fenen_US
dc.date.accessioned2020-01-02T00:04:19Z-
dc.date.available2020-01-02T00:04:19Z-
dc.date.issued2019-11-01en_US
dc.identifier.urihttp://dx.doi.org/10.3390/math7111097en_US
dc.identifier.urihttp://hdl.handle.net/11536/153373-
dc.description.abstractFall detection is a critical task in an aging society. To fulfill this task, smart technology applications have great potential. However, it is not easy to choose a suitable smart technology application for fall detection. To address this issue, a fuzzy collaborative intelligence approach is proposed in this study. In the fuzzy collaborative intelligence approach, alpha-cut operations are applied to derive the fuzzy weights of criteria for each decision maker. Then, fuzzy intersection is applied to aggregate the fuzzy weights derived by all decision makers. Subsequently, the fuzzy technique for order preference by similarity to the ideal solution is applied to assess the suitability of a smart technology application for fall detection. The fuzzy collaborative intelligence approach is a posterior-aggregation method that guarantees a consensus exists among decision makers. After applying the fuzzy collaborative intelligence approach to assess the suitabilities of four existing smart technology applications for fall detection, the most and least suitable smart technology applications were smart carpet and smart cane, respectively. In addition, the ranking result using the proposed methodology was somewhat different from those using three existing methods.en_US
dc.language.isoen_USen_US
dc.subjectfall detectionen_US
dc.subjectsmart technologyen_US
dc.subjectfuzzy collaborative intelligenceen_US
dc.subjectfuzzy technique for order preference by similarity to ideal solutionen_US
dc.subjectTOPSISen_US
dc.titleEvaluating the Suitability of a Smart Technology Application for Fall Detection Using a Fuzzy Collaborative Intelligence Approachen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/math7111097en_US
dc.identifier.journalMATHEMATICSen_US
dc.citation.volume7en_US
dc.citation.issue11en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000502288700094en_US
dc.citation.woscount0en_US
Appears in Collections:Articles