Results 231 to 240 of about 2,268,403 (339)

Performance Monitoring of Photovoltaic Modules Using Machine‐Learning‐Based Solutions: A Survey of Current Trends

Energy Science &Engineering, EarlyView.
The graphical abstract presents the concept of applying machine‐learning algorithms to assess the performance of photovoltaic modules. Data from solar panels are fed to surrogates of intelligent models, to assess the following performance metrics: identifying faults, quantifying energy production and trend degradation over time. The combination of data
Nangamso Nathaniel Nyangiwe, Abraham Dimitri Kapim Kenfack, Nicolas Thantsha, Mandla Msimanga   +3 more
wiley   +1 more source

MDAPT: Multi-Modal Depth Adversarial Prompt Tuning to Enhance the Adversarial Robustness of Visual Language Models. [PDF]

Sensors (Basel)
Li C, Liao Y, Ding C, Ye Z.
europepmc   +1 more source

From Gradients to Gains: Empowering Rgb-T Tracker with Adversarially Robust Data

Jianqiang Li, Tao Chen
openalex   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Security in Transformer Visual Trackers: A Case Study on the Adversarial Robustness of Two Models. [PDF]

Sensors (Basel)
Ye P, Chen Y, Ma S, Xue F, Crespi N, Chen X, Fang X.   +6 more
europepmc   +1 more source

The Dilemma Between Dimensionality Reduction and Adversarial Robustness. [PDF]

, 2020
Sheila Alemany, Niki Pissinou
openalex  

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Improving Adversarial Robustness of ECG Classification Based on Lipschitz Constraints and Channel Activation Suppression. [PDF]

Sensors (Basel)
Chen X, Si Y, Zhang Z, Yang W, Feng J.
europepmc   +1 more source

A Deep Neural Network Based on Two‐Stage Training for Estimating Heart Rate Variability From Camera Videos

Health Care Science, EarlyView.
Heart Rate Variability Estimation from Camera Videos ABSTRACT Background Studies have shown that heart rate variability (HRV) is a predictor of the prognosis of cardiovascular diseases. Contact heartbeat monitoring equipment is widely used, especially in hospitals, and benefits from the rapidity and accuracy of the detection of physiological health ...
Lan Lan, Jin Yin, Haohan Zhang, Hua Jiang, Rui Qin, Xia Zhao, Yu Zhang, Yilong Wang, Jiajun Qiu   +8 more
wiley   +1 more source