Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7557
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dc.contributor.authorYang, Rongen_US
dc.contributor.authorWang, Zhen yuanen_US
dc.contributor.authorHeng, Peng-Annen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-23T05:21:33Z-
dc.date.available2023-03-23T05:21:33Z-
dc.date.issued2008-
dc.identifier.citationIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2008, Vol. 38 (2), pp. 367 - 380en_US
dc.identifier.issn10834419-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7557-
dc.description.abstractIn this paper, the original Choquet integral is generalized as a Fuzzified Choquet Integral with a Fuzzy-valued Integrand (FCIFI), which supports a fuzzy-valued integrand and an integration result. The calculation of the FCIFI is established on the Choquet integral with an interval-valued integrand (CIII). The definitions, properties, and calculation algorithms of the CIII and the FCIFI are discussed and proposed in this paper. As a specific application scheme, we designed a CIII regression model for the regression problems involving interval-valued data. This CIII regression model has a self-learning ability through a double genetic algorithm. Finally, a daily temperature predictor based on the CIII regression model is discussed, where a series of experiments is implemented to validate the performance of the predictor by real weather records from the Hong Kong Observatory. © 2008 IEEE.en_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cyberneticsen_US
dc.titleFuzzified choquet integral with a fuzzy-valued integrand and its application on temperature predictionen_US
dc.typePeer Reviewed Journal Articleen_US
dc.identifier.doi10.1109/TSMCB.2007.911377-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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