A dynamic broad TSK fuzzy classifier based on iterative learning on progressively rebalanced data
Most of the existing class imbalanced classification methods are weak in interpretability,
which is necessary for models to be convincing in some specific scenarios. In this study, we …
which is necessary for models to be convincing in some specific scenarios. In this study, we …
Genetic Fuzzy Route Prediction and Interception Through Emulation of Evader Control Logic
D Heitmeyer - 2024 - search.proquest.com
The integration of AI in autonomous vehicles has been rapidly expanding and has the
potential to raise concerns about non-compliant or malicious actors. Predicting movements …
potential to raise concerns about non-compliant or malicious actors. Predicting movements …
[PDF][PDF] Coronavirus risk factor by Sugeno fuzzy logic
SQ Hasan, RRO Al-Nima, SE Mahmmod - Int J Artif Intell ISSN - researchgate.net
World recently faced big challenges with the pandemic of coronavirus disease 2019 (COVID-
19). Governments suffer from the problem of appropriately identifying the risk factor of this …
19). Governments suffer from the problem of appropriately identifying the risk factor of this …
Dynamic-Static Siamese Takagi-Sugeno-Kang Fuzzy System with Inductive-Reflection Deep Fuzzy Rule
Q Shi, Y Jiang, Q Shen, J Lou - papers.ssrn.com
Abstract The first-order Takagi-Sugeno-Kang (TSK) fuzzy classifiers are famous for their high
computational efficiency and strong interpretability, but they often struggle to learn from …
computational efficiency and strong interpretability, but they often struggle to learn from …