An improved alpha-cut approach to transforming fuzzy membership function into basic belief assignment

作者：Yi, Yang; Li, X. Rong; Han Deqiang^*

来源：Chinese Journal of Aeronautics, 2016, 29(4): 1042-1051.

DOI：10.1016/j.cja.2016.03.007

• Belief functions
• Evidence theory
• Fuzzy sets
• Membership functions
• Uncertainty

In practical applications, pieces of evidence originated from different sources might be modeled by different uncertainty theories. To implement the evidence combination under the Dempster-Shafer evidence theory (DST) framework, transformations from the other type of uncertainty representation into the basic belief assignment are needed. alpha-Cut is an important approach to transforming a fuzzy membership function into a basic belief assignment, which provides a bridge between the fuzzy set theory and the DST. Some drawbacks of the traditional alpha-cut approach caused by its normalization step are pointed out in this paper. An improved alpha-cut approach is proposed, which can counteract the drawbacks of the traditional alpha-cut approach and has good properties. Illustrative examples, experiments and related analyses are provided to show the rationality of the improved alpha-cut approach.

• 出版日期2016-8
• 单位西安交通大学