Machine learning methods for fault diagnosis in ac microgrids: A systematic review

MM Zaben, MY Worku, MA Hassan, MA Abido - IEEE access, 2024 - ieeexplore.ieee.org
AC microgrids are becoming increasingly important for providing reliable and sustainable
power to communities. However, the evolution of distribution systems into microgrids has …

Hydropower operation optimization using machine learning: A systematic review

J Bernardes Jr, M Santos, T Abreu, L Prado Jr… - AI, 2022 - mdpi.com
The optimal dispatch of hydropower plants consists of the challenge of taking advantage of
both available head and river flows. Despite the objective of delivering the maximum power …

Dynamic programming with successive approximation and relaxation strategy for long-term joint power generation scheduling of large-scale hydropower station group

Z He, C Wang, Y Wang, B Wei, J Zhou, H Zhang, H Qin - Energy, 2021 - Elsevier
The joint optimal operation of large-scale hydropower station group (LHSG) is faced with the
higher dimension than that of cascade hydropower station, the demand for the efficient …

Cognitive Digital Twins of the natural environment: Framework and application

J Feng, H Tang, S Zhou, Y Cai, J Zhang - Engineering Applications of …, 2025 - Elsevier
Digital Twin (DT) technology offers a method of creating digital models of natural systems to
enhance their ability to withstand natural disasters. Currently, DT of the natural environment …

Online state-of-health estimation for second-use lithium-ion batteries based on weighted least squares support vector machine

W Xiong, Y Mo, C Yan - Ieee Access, 2020 - ieeexplore.ieee.org
Online state-of-health (SOH) estimation is critical for second-use retired lithium-ion batteries.
However, the SOH of retired batteries is highly nonlinear, and the existing degradation trend …

Effective stochastic streamflow simulation method based on Gaussian mixture model

B Jia, J Zhou, Z Tang, Z Xu, X Chen, W Fang - Journal of Hydrology, 2022 - Elsevier
Stochastic simulations of streamflow sequences are essential for water resource planning
and management. In this study, a new Gaussian mixture model (GMM)-based method is …

Risk assessment of multireservoir joint flood control system under multiple uncertainties

Q Wang, J Zhou, L Dai, K Huang… - Journal of Flood Risk …, 2021 - Wiley Online Library
Multireservoir joint flood control operation is an important nonstructural measure for flood
control in some basins. Owing to the existence of uncertainties in flood control operation …

An hierarchical approach for automatic segmentation of leaf images with similar background using kernel smoothing based Gaussian process regression

ES Gopi - Ecological Informatics, 2021 - Elsevier
Real-time automation of leaf image segmentation is a difficult task when there are similar
leaves in the background, particularly in leaf images captured in the cultivation fields. These …

Intelligent identification of effective reservoirs based on the random forest classification model

J Li, P Zhong, M Yang, F Zhu, J Chen, W Liu, S Xu - Journal of Hydrology, 2020 - Elsevier
In the real-time operation of a flood control system, identifying effective reservoirs accurately
and adaptively is the premise of establishing a multi-reservoir real-time flood control hybrid …

Knowledge-Informed Data-Driven Modeling of Coupled Human-Built–Natural Systems: The Case of Hurricane-Induced Debris

C González-Dueñas, MM Meads, JE Padgett… - Natural Hazards …, 2023 - ascelibrary.org
Debris is one of the most challenging cascading effects posed by hurricane events, causing
large financial and logistical burdens to coastal communities. Moreover, disaster debris can …