Anti-deactivation of zeolite catalysts for residue fluid catalytic cracking

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Y Li, M Liang, H Li, Z Yang, L Du, Z Chen - Engineering Applications of …, 2023 - Elsevier
Perceiving the future trend of Vessel Traffic Flow (VTF) in advance has great application
values in the maritime industry. However, using such big data from the Automatic …

Deep learning in the grading of diabetic retinopathy: A review

NMA Tajudin, K Kipli, MH Mahmood, LT Lim… - IET Computer …, 2022 - Wiley Online Library
Diabetic Retinopathy (DR) grading into different stages of severity continues to remain a
challenging issue due to the complexities of the disease. Diabetic Retinopathy grading …

LBE corrosion fatigue life prediction of T91 steel and 316 SS using machine learning method assisted by symbol regression

S Feng, X Sun, G Chen, H Wu, X Chen - International Journal of Fatigue, 2023 - Elsevier
This study employs machine learning models assisted by symbol regression to achieve
satisfactory corrosion fatigue life prediction for T91 steel and 316L stainless steel (SS) used …

Alzheimer's disease diagnosis via intuitionistic fuzzy random vector functional link network

AK Malik, MA Ganaie, M Tanveer… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a prominent neurodegenerative disorder, which leads to
memory loss and cognitive impairment. The progression is irreversible and shows atrophies …

Affinity based fuzzy kernel ridge regression classifier for binary class imbalance learning

BB Hazarika, D Gupta - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
The class imbalance learning (CIL) problem indicates when one class have very low
proportions of samples (minority class) compared to the other class (majority class). Even …

Graph embedded intuitionistic fuzzy random vector functional link neural network for class imbalance learning

MA Ganaie, M Sajid, AK Malik… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The domain of machine learning is confronted with a crucial research area known as class
imbalance (CI) learning, which presents considerable hurdles in the precise classification of …