Abstract
This paper presents two extended fuzzy integrals under rough uncertainty, i.e. rough upper fuzzy and lower fuzzy integrals, and extended properties are also given. Furthermore, these two integrals are applied here in information fusion and classification processes for rough features, and the corresponding extended models are also proposed. These types of integrals generalize fuzzy integrals and enlarge their domains of applications in fusion and classification under rough uncertainty. Examples show that they fuse or classify objects with rough features with fairly good effects while the existed methods based on reals can not solve.
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Guan, T., Feng, B. (2004). Rough Fuzzy Integrals for Information Fusion and Classification. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_43
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DOI: https://doi.org/10.1007/978-3-540-25929-9_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22117-3
Online ISBN: 978-3-540-25929-9
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