Data Processing under Fuzzy Uncertainty: Towards More Efficient Algorithms
Hung Tan Nguyen, Olga M. Kosheleva, Владик Крейнович · 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · 2022
In many practical situations, we need to process data under fuzzy uncertainty: we have fuzzy information about the algorithm’s input, and we want to find the resulting information about the algorithm’s output. It is known that this problem can be reduced to computing the range of the algorithm over several (A) alpha-cuts of the input. However, a straightforward application of this idea requires A times longer computation time than each range estimation – and for complex data processing algorithms, each range computation is already time-consuming. In this paper, we show how to compute all the desired ranges much faster.