Double AMIS-ensemble deep learning for skin cancer classification
This study aims to create a precise skin cancer classification system (SC-CS) able to
distinguish various skin cancer types. Targeted categories include melanoma, vascular …
distinguish various skin cancer types. Targeted categories include melanoma, vascular …
Reinforcement learning for autonomous process control in industry 4.0: Advantages and challenges
N Nievas, A Pagès-Bernaus, F Bonada… - Applied Artificial …, 2024 - Taylor & Francis
In recent years, the integration of intelligent industrial process monitoring, quality prediction,
and predictive maintenance solutions has garnered significant attention, driven by rapid …
and predictive maintenance solutions has garnered significant attention, driven by rapid …
Intelligent fault diagnosis for air handing units based on improved generative adversarial network and deep reinforcement learning
Data-driven Automatic fault detection and diagnosis (AFDD) for air handling units (AHUs) is
crucial for ensuring the stable operation and energy consumption of the heating ventilation …
crucial for ensuring the stable operation and energy consumption of the heating ventilation …
Applications of deep reinforcement learning in nuclear energy: A review
Y Liu, B Wang, S Tan, T Li, W Lv, Z Niu, J Li… - … Engineering and Design, 2024 - Elsevier
In recent years, Deep reinforcement learning (DRL), as an important branch of artificial
intelligence (AI), has been widely used in physics and engineering domains. It combines the …
intelligence (AI), has been widely used in physics and engineering domains. It combines the …
A deep reinforcement learning-based intelligent fault diagnosis framework for rolling bearings under imbalanced datasets
Y Li, Y Wang, X Zhao, Z Chen - Control Engineering Practice, 2024 - Elsevier
Deep learning is a commonly employed technique for fault diagnosis; however, its
effectiveness is contingent upon the presence of balanced data. In real-world industrial …
effectiveness is contingent upon the presence of balanced data. In real-world industrial …
KPCA-based fault detection and diagnosis model for the chemical and volume control system in nuclear power plants
Y Sun, M Song, C Song, M Zhao, Y Yang - Annals of Nuclear Energy, 2025 - Elsevier
To study the fault intelligent detection and diagnosis method of nuclear power plant systems
and improve the detection and diagnosis effect of internal fault of nuclear power plant …
and improve the detection and diagnosis effect of internal fault of nuclear power plant …
A heterogeneous transfer learning method for fault prediction of railway track circuit
Prediction and identification of faults in track circuits are crucial for improving the safety and
efficiency of railway transportation. However, due to the absence of real data, the task of …
efficiency of railway transportation. However, due to the absence of real data, the task of …
Application of reinforcement learning to deduce nuclear power plant severe accident scenario
SH Song, Y Lee, JY Bae, KS Song, MR Seo… - Annals of Nuclear …, 2024 - Elsevier
Severe accident scenarios for nuclear power plants are determined through probabilistic
safety analysis (PSA). In this process, it is possible to identify the failure sequence of specific …
safety analysis (PSA). In this process, it is possible to identify the failure sequence of specific …
A Comparative Study of Semi-Supervised Anomaly Detection Methods for Machine Fault Detection
D Neupane, MR Bouadjenek… - PHM Society …, 2024 - papers.phmsociety.org
Industrial automation has extended machines' runtime, thereby raising breakdown risks.
Machine breakdowns not only have economic and productivity consequences, but they can …
Machine breakdowns not only have economic and productivity consequences, but they can …
Intelligent multi-severity nuclear accident identification under transferable operation conditions
S Xu, Y Yao, N Yong, D Xia, D Ge, J Yu - Annals of Nuclear Energy, 2024 - Elsevier
Nuclear power plants (NPPs) have witnessed significant advancements in intelligent
accident identification in recent years. However, comprehensive research on fine-grained …
accident identification in recent years. However, comprehensive research on fine-grained …