Enhancing Interval Type-2 Fuzzy Logic Systems: Learning for Precision and Prediction Intervals
Author:
Affiliation:
1. Istanbul Technical University,Control and Automation Eng. Dept.,Istanbul,Türkiye
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10609967/10611747/10612062.pdf?arnumber=10612062
Reference19 articles.
1. High-quality prediction intervals for deep learning: A distribution-free, ensembled approach;Pearce,2018
2. A review of uncertainty quantification in deep learning: Techniques, applications and challenges
3. Uncertain Rule-Based Fuzzy Systems
4. More Than Accuracy: A Composite Learning Framework for Interval Type-2 Fuzzy Logic Systems
5. Recent advances in neuro-fuzzy system: A survey
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Hardware architecture and memristor-crossbar implementation of type-2 fuzzy system with type reduction and in-situ training;The Journal of Supercomputing;2024-07-02
2. Zadeh's Type-2 Fuzzy Logic Systems: Precision and High-Quality Prediction Intervals;2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE);2024-06-30
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