Abstract Interval-valued fuzzy reasoning plays a vital role in intelligent systems with the performance of effectively reducing the loss of fuzzy information and reflecting the vagueness and uncertainty in information processing. However the existing reasoning algorithms were developed based on some special interval-valued t-norms which limits the usability and adaptation of these algorithms. This study proposes general reasoning algorithms on the basis of interval-valued fuzzy sets, that is the interval-valued fuzzy reasoning triple I algorithms based on the left-continuous t-representable t-norm T T 1 , T 2 . Furthermore, the interval-valued R -type triple I solutions of the interval-valued fuzzy reasoning triple I algorithms are given. We show that the proposed algorithms possess the reducibility. Finally, some robustness results of the interval-valued fuzzy reasoning triple I algorithms based on the left-continuous interval-valued t-representable t-norm are proved.

中文翻译：

---

基于t-可表示t-范数的区间值模糊推理全蕴涵算法

摘要 区间值模糊推理在智能系统中起着至关重要的作用，其性能有效地减少了模糊信息的损失，反映了信息处理中的模糊性和不确定性。然而，现有的推理算法是基于一些特殊的区间值 t 范数开发的，这限制了这些算法的可用性和适应性。本研究提出了基于区间值模糊集的通用推理算法，即基于左连续t-可表示t-范数TT 1 ，T 2 的区间值模糊推理三元组I算法。此外，给出了区间值模糊推理三I算法的区间值R型三I解。我们表明所提出的算法具有可约性。最后，