Abstract
The Bonferroni mean is a traditional mean type aggregation operator bounded by the max and min operators, which is suitable to aggregate the crisp data. In this paper, we consider situations where the input data are interval numbers. We develop some uncertain Bonferroni mean operators, and then combine them with the well-known ordered weighted averaging operator and Choquet integral respectively for aggregating uncertain information. We also give their applications to multi-criteria decision making under uncertainty, and finally, some possible extensions for further research are discussed.
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More From: International Journal of Computational Intelligence Systems
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