Abstract
Intuitionistic fuzzy values (IFVs), each of which consists of a membership degree, a non-membership degree, and a hesitancy degree, are a powerful tool to depict uncertain or fuzzy information. In many fields, such as decision making, cluster analysis, and information retrieval, etc., information aggregation is an essential process. Therefore, how to aggregate IFVs is an interesting and important research topic, which has received great attention from researchers and a lot of intuitionistic fuzzy aggregation techniques have been developed. This chapter offers a systematic introduction to the latest research results in intuitionistic fuzzy aggregation, the extended results in interval-valued intuitionistic fuzzy environments, and their applications in multi-attribute decision making.
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© 2012 Springer-Verlag Berlin Heidelberg
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Xu, Z. (2012). Intuitionistic Fuzzy Aggregation Techniques. In: Intuitionistic Fuzzy Aggregation and Clustering. Studies in Fuzziness and Soft Computing, vol 279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28406-9_1
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DOI: https://doi.org/10.1007/978-3-642-28406-9_1
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28405-2
Online ISBN: 978-3-642-28406-9
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