Results 191 to 200 of about 30,442 (292)

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

Generative AI as a transformational logic for cognitive neuroscience. [PDF]

Commun Biol
Beste C, Safavi S.
europepmc   +1 more source

Smart Parking Systems: A Review of Optimization Techniques and Technological Advances

Energy Science &Engineering, EarlyView.
This review highlights optimization techniques and recent technological advances in smart parking systems, emphasizing their role in enhancing efficiency, reducing congestion, and improving user experience. It provides insights into innovative approaches that shape the future of sustainable and intelligent urban mobility. ABSTRACT In heavily populated,
Amirhossein Khosravi Sarvenoee, Mohammad Kohzadipour, Majid Valizadeh, Mohammad Saeedi Kia, Milad Karimian, Mohammad Sharifirad   +5 more
wiley   +1 more source

Coal Calorific Value Prediction via Multi-View Transformer. [PDF]

Sensors (Basel)
Zhang D, Li J, Tian Z, Guo Y, Ren X, Ren W, Li X, Zhang P.   +7 more
europepmc   +1 more source

Hybrid Temporal Autoencoder and Similarity Matching for Low Aggregation Level Long Time Series Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT Deep learning‐based long time series forecasting (LTSF) has achieved high accuracy by effectively capturing the underlying trends, seasonality, and temporal dependencies within time series data. However, at the individual entity level, termed the low aggregation level (LAL), intermittency, irregularity, and data sparsity undermine the ...
Hanbyeol Park, Sunghyun Sim, Kikun Park, Yongjae Lee, Eunhee Park, Hyerim Bae   +5 more
wiley   +1 more source

Application of Sparse Autoencoders to Enhance Mechanistic Interpretability of Large Language Models in Medicine. [PDF]

JMIR AI
Metzger A, Patil S, Sugarmann LR, Karabacak M, Margetis K.   +4 more
europepmc   +1 more source

MARS‐Diff: Guarded Residual Diffusion for Leakage‐Disciplined Probabilistic Portfolio‐Loss Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT This paper develops Masked Asset–Regime Scenario Diffusion (MARS‐Diff), a leakage‐disciplined framework for probabilistic forecasting of multiday portfolio losses. The framework combines a regularized heterogeneous autoregressive model with exogenous predictors (HAR‐X) as its anchor, a train‐only masked representation of a high‐dimensional ...
Çağlar Sözen, Mervenur Sözen
wiley   +1 more source

RRAEDy: adaptive latent linearization of nonlinear dynamical systems. [PDF]

Sci Rep
Mounayer J, Rodriguez S, Tomezyk J, Ghnatios C, Chinesta F.   +4 more
europepmc   +1 more source

Recent Paradigms in Nanomaterial‐Assisted Electrochemical (Bio) Sensing for Food Quality and Safety Analysis: A Critical Review

Food Safety and Health, EarlyView.
ABSTRACT Rising global demand for safe and unadulterated foods has accelerated the need for rapid, low‐cost, and portable analytical technologies. Traditional laboratory methods, although accurate, are often labor‐intensive and unsuitable for decentralized, real‐time monitoring. In response, nanomaterial‐assisted electrochemical sensors have emerged as
Toleshi Teshome
wiley   +1 more source

Robust unsupervised outlier detection in IoT using contrastive learning-driven autoencoders. [PDF]

Sci Rep
Gu S.
europepmc   +1 more source