Results 171 to 180 of about 3,187,155 (299)

Minimizing Stochastic Complexity with Ridge Regression. [PDF]

Entropy (Basel)
Mizzi A, Walker DM, Small M.
europepmc   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

Concentration-to-dose ratio as a predictor of lacosamide efficacy in Chinese children with epilepsy: a single-center retrospective cohort study. [PDF]

Front Pharmacol
Du Z, Wang Y, Nie G, Liu M, Li Y, Wang J.   +5 more
europepmc   +1 more source

Triggered Calcium Lightning Programs Cochlear Development

Exploration, EarlyView.
Summary: Before the onset of hearing, the developing inner ear generates spontaneous calcium signals that are thought to guide maturation. In this study, we discovered a rapid and widespread calcium flash—dubbed “Ca2+ lightning”—originating from supporting cells beneath the sensory hair cells, which triggers coordinated calcium waves across the entire ...
Qiang Ma, Hai‐Peng Wang, Yu‐Meng Jiang, Ke Lai, Ming‐Xian Li, Zhen Zhang, Li‐Na Gong, Jing‐Wei Lai, Kai‐Ming Su, Lu‐Yang Wang, Hui Wang, Shan‐Kai Yin, Hao He, Hai‐Bo Shi   +13 more
wiley   +1 more source

High-Accuracy Machine Learning Projections of Composition-Dependent Thermal Stability in Halide Perovskites. [PDF]

Adv Mater
Hering AR, Dubey M, Hosseini E, Srivastava M, An Y, Correa-Baena JP, Homayoun H, Leite MS.   +7 more
europepmc   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

NeuroFusion: A Unified Framework for Generalized Visual Stimulus Decoding from fMRI Across Datasets and Subjects. [PDF]

Neuroinformatics
Kashif M, Ferrante M, Toschi N.
europepmc   +1 more source

A New Implementation of Network GARCH Model for Stock Volatility and Co‐Volatility Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT Volatility clustering and spillovers are key features of financial time series with many cross‐sectional assets. While network analysis links similar or correlated stocks and helps trace volatility spillovers, contemporary multivariate ARCH‐GARCH formulations struggle to represent structured network dependence and remain parsimonious.
Peiyi Zhou
wiley   +1 more source

A Physics-Informed Machine Learning Framework for Modeling Biaxial Strain-Induced Band Gap Variation in Zig-Zag Single-Walled Carbon Nanotubes. [PDF]

Nanomaterials (Basel)
Vardar N.
europepmc   +1 more source

Beta Forecasting With Realized Beta Estimators and Machine Learning Algorithms

Journal of Forecasting, EarlyView.
ABSTRACT This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Higher levels of beta forecast accuracy are demonstrated, relative to other studies in the literature. These improvements are also highly significant, both statistically and economically.
Bao Doan, Dulani Jayasuriya, John B. Lee, Jonathan J. Reeves   +3 more
wiley   +1 more source