Results 141 to 150 of about 128,746 (262)

Neural Network Models for Solar Irradiance Forecasting in Polluted Areas: A Comparative Study

Energy Science &Engineering, EarlyView.
Pollution‐aware hybrid ensemble model is proposed to forecast solar irradiance across eight diverse cities. The model integrates MLP, RNN, and NARX to handle varying atmospheric pollution levels. The model outperforms state‐of‐the‐art methods with enhanced accuracy and interpretability on standard solar irradiance data set.
Mujtaba Ali, Muhammad Yaqoob Javed, Aamer Bilal Asghar, Khurram Hashmi, Abbas Javed, Basem Alamri, Krzysztof Ejsmont   +6 more
wiley   +1 more source

Generative Adversarial Networks for Modeling Bio-Electric Fields in Medicine: A Review of EEG, ECG, EMG, and EOG Applications. [PDF]

Bioengineering (Basel)
Liang J, Zhou Y, Ma K, Jia Y, Zhang Y, Han B, Xiang M.   +6 more
europepmc   +1 more source

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

Dynamic Contrast-enhanced MRI for Evaluating Breast Cancer Chemotherapy Response Using Conditional Generative Adversarial Networks. [PDF]

Radiol Imaging Cancer
Arledge CA, Zhao AH, Topaloglu U, Zhao D.   +3 more
europepmc   +1 more source

Imbalanced Spectral Data Analysis using Data Augmentation based on the Generative Adversarial Network [PDF]

Jihoon Chung, Junru Zhang, Amirul Islam Saimon, Yang Liu, Blake N. Johnson, Zhenyu Kong   +5 more
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

Forecasting the diabetic retinopathy progression using generative adversarial networks. [PDF]

Commun Med (Lond)
Qiao H, Tang F, Zhou H, Cai Y, Guo K, Wang J, Ma T, Ju L, Feng W, Ma Z, Chen J, Luo Y, Wang B, Ge Z, Yang Q.   +14 more
europepmc   +1 more source

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

Towards an optimized paradigm: generative adversarial networks and 3D modeling in landscape design and generation. [PDF]

PLoS One
He M.
europepmc   +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