Results 241 to 250 of about 11,734,216 (296)

Influenza-Like Illness Forecasting Using Multisource Data: Comparative Deep Learning Study. [PDF]

JMIR Med Inform
Dang C, Tong Y, Mo Y, Zhao Z, Li S, Liu F, Jia H, Zhao J, Xu Y, Chen H.   +9 more
europepmc   +1 more source

Attention‐Based Spatial–Temporal Model for the Entire Indoor Space Temperature Estimation

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
This study proposes a novel attention‐based spatial–temporal model for indoor temperature estimation, which integrates positional encoding and an attention mechanism with a fully connected neural network. By jointly capturing temporal dynamics and spatial correlations, the model enables high‐resolution estimation of temperature fields across the entire
Goro Terumichi, Jiarui Li, Tatsuji Kimura, Hiroaki Nishi   +3 more
wiley   +1 more source

Two-stage transformer encoder and attention-guided GRU-based residual correction for short-term load forecasting. [PDF]

Front Artif Intell
Chandrasekaran R, Paramasivan SK.
europepmc   +1 more source

A Spatio‐Temporal Dynamics Model for Indoor Environmental Forecasting

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Accurate forecasting of indoor environmental conditions is essential for intelligent building operations and comfort‐oriented controls. However, reliable prediction remains challenging due to spatial heterogeneity across sensing locations, complex multi‐modal interactions, and nonstationary temporal dynamics.
Goro Terumichi, Jiarui Li, Tatsuji Kimura, Hiroaki Nishi   +3 more
wiley   +1 more source

Time-Aware and Power-Law Retention Gating Mechanisms in LSTMs for Irregularly Sampled Sensor Data: A Survey. [PDF]

Sensors (Basel)
Das D, Adams SD, Corva DM, Bucknall TK, Kouzani AZ.   +4 more
europepmc   +1 more source

NanoSentry: An Edge‐Deployable Unified Neural Architecture for Multi‐Domain Industrial Prognostics and Health Management

Artificial Intelligence for Engineering, EarlyView.
NanoSentry, a sub‐50 KiB unified architecture for multi‐domain prognostics, matches or outperforms models 4.5× $4.5\times $ larger across turbofan, battery, and bearing benchmarks while reducing end‐of‐life prediction error up to 5.8× $5.8\times $. Physical STM32H7 deployment confirms sub‐3 ms inference and up to 26 KiB peak SRAM without quantisation ...
Naem Azam Chowdhury, Abu Nasek, Khan Prottoy, Md Hamid Borkot Tulla, Jafor Sadik Chowdhury   +4 more
wiley   +1 more source

Stock-level volatility forecasting using machine learning: A comparative study of GARCH, Random Forest, LSTM, and GRU on US Equities. [PDF]

PLoS One
Pragadeeshwaran RV, Tarun Narayanan R, Bhavadharini RM.   +2 more
europepmc   +1 more source

A deep learning approach to mild cognitive impairment detection from electroencephalogram signals. [PDF]

Dement Neuropsychol
Ohal HS, Mantri S.
europepmc   +1 more source

ECG‐TransCovNet: A hybrid transformer model for accurate arrhythmia detection using Electrocardiogram signals

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Abnormalities in the heart's rhythm, known as arrhythmias, pose a significant threat to global health, often leading to severe cardiac conditions and sudden cardiac deaths. Therefore, early and accurate detection of arrhythmias is crucial for timely intervention and potentially life‐saving treatment.
Hasnain Ali Shah, Faisal Saeed, Muhammad Diyan, Nouf Abdullah Almujally, Jae‐Mo Kang   +4 more
wiley   +1 more source

Research on a lead-acid battery fault detection method based on LSTM-AE-Cosine. [PDF]

PLoS One
Liu L, Xu H, Tang H, Cui J, Feng L, Deng K.   +5 more
europepmc   +1 more source