Graph attention-based U-net conditional generative adversarial networks for the identification of synchronous generation unit parameters
L Yin, W Zhao - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
After generation units are connected to the power grid, electrical parameters such as
generation unit output voltage, current and power need to be monitored for the safe and …
generation unit output voltage, current and power need to be monitored for the safe and …
[HTML][HTML] Graphical Feature Construction-Based Deep Learning Model for Fatigue Life Prediction of AM Alloys
H Wu, A Wang, Z Gan, L Gan - Materials, 2024 - mdpi.com
Fatigue failure poses a serious challenge for ensuring the operational safety of critical
components subjected to cyclic/random loading. In this context, various machine learning …
components subjected to cyclic/random loading. In this context, various machine learning …
[HTML][HTML] Fusion of heterogeneous industrial data using polygon generation & deep learning
Abstract Analysis of industrial data imposes several challenges. These data are acquired
from heterogeneous sources such as sensors, cameras, IoT, etc, and are stored in different …
from heterogeneous sources such as sensors, cameras, IoT, etc, and are stored in different …
Polygon generation and video-to-video translation for time-series prediction
M Elhefnawy, A Ragab, MS Ouali - Journal of Intelligent Manufacturing, 2023 - Springer
This paper proposes an innovative method for time-series prediction in energy-intensive
industrial systems characterized by highly dynamic non-linear operations. The proposed …
industrial systems characterized by highly dynamic non-linear operations. The proposed …
Alternate inference-decision reinforcement learning with generative adversarial inferring for bridge bidding
J Wang, S Wang, T Xu - Neural Computing and Applications, 2024 - Springer
Contract bridge is a competitive-cooperative multiplayer game. In the bidding phase, the
decision-making process is complex, given the extensive range of inaccessible information …
decision-making process is complex, given the extensive range of inaccessible information …
On the Use of Graphical Features for Fatigue Life Prediction with Machine Learning
H Wu, AB Wang, Z Gan, P Zhang, L Gan - Available at SSRN 4948967 - papers.ssrn.com
Fatigue failure poses a serious challenge for ensuring the operational safety of critical
components subjected to alternating loading. In this respect, various machine learning (ML) …
components subjected to alternating loading. In this respect, various machine learning (ML) …