Results 221 to 230 of about 90,690 (297)

Data-driven prediction of future purchase behavior in cross-border e-commerce using sequence modeling with PSO-tuned LSTM. [PDF]

PLoS One
Yang Y.
europepmc   +1 more source

Ensemble Kalman filter in latent space using a variational autoencoder pair

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The use of the ensemble Kalman filter (EnKF) in strongly nonlinear or constrained atmospheric, oceanographic, or sea‐ice models can be challenging. Applying the EnKF in the latent space of a variational autoencoder (VAE) ensures that the ensemble members satisfy the balances and constraints present in the model.
Ivo Pasmans, Yumeng Chen, Tobias Sebastian Finn, Marc Bocquet, Alberto Carrassi   +4 more
wiley   +1 more source

A Hybrid CNN-LSTM Architecture for Seismic Event Detection Using High-Rate GNSS Velocity Time Series. [PDF]

Sensors (Basel)
Başar D, Çelik RN.
europepmc   +1 more source

Integrating LSTM and Hybrid Methods for Automatic Balinese Script Transcription

Made Sudarma
openalex   +2 more sources

Achieving Predictive Precision: Leveraging LSTM and Pseudo Labeling for Volvo's Discovery Challenge at ECML-PKDD 2024 [PDF]

Carlo Metta, Marco Gregnanin, Andrea Papini, Silvia Giulia Galfrè, Andrea Fois, Francesco Morandin, Marco Fantozzi, Maurizio Parton   +7 more
openalex   +1 more source

An Interpretable TCN– Transformer Framework for Lithium‐Ion Battery State of Health Estimation Using SHAP Analysis

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Accurate state of health (SOH) estimation of Li‐ion batteries is essential for ensuring safety, reliability, and prolonging battery lifespan in energy storage systems and electric vehicles. This study proposes a hybrid temporal convolutional network (TCN)–transformer framework that effectively captures both short‐term temporal dynamics and ...
Fusen Guo, Zhibo Zhang, Xuzhe Ma, Lin Li, Hailing Zhou, Chaojie Li, Huadong Mo   +6 more
wiley   +1 more source

Hybrid Unsupervised-Supervised Learning Framework for Rainfall Prediction Using Satellite Signal Strength Attenuation. [PDF]

Sensors (Basel)
Laon P, Sahavisit T, Pourbunthidkul S, Puangragsa S, Wichittrakarn P, Phasukkit P, Houngkamhang N.   +6 more
europepmc   +1 more source

Gla-Sdp: A Novel Attention-Based Semantic and Static Feature Fusion Method Using Gcn and Lstm for Software Defect Prediction

Haining Meng, Han Wu, Xiaoqing Li, Xinhong Hei   +3 more
openalex   +1 more source

From “Mirror Flower, Water Moon” to Multi‐Task Visual Prospective Representation Learning for Unmanned Aerial Vehicles Indoor Mapless Navigation

Journal of Field Robotics, EarlyView.
ABSTRACT Vision‐based deep learning models have been widely adopted in autonomous agents, such as unmanned aerial vehicles (UAVs), particularly in reactive control policies that serve as a key component of navigation systems. These policies enable agents to respond instantaneously to dynamic environments without relying on pre‐existing maps.
Yingxiu Chang, Yongqiang Cheng, John Murray, Muhammad Khalid, Umar Manzoor   +4 more
wiley   +1 more source

TCN-LSTM-AM Short-Term Photovoltaic Power Forecasting Model Based on Improved Feature Selection and APO. [PDF]

Sensors (Basel)
Ye N, Zhi C, Yu Y, Lin S, Liu F.
europepmc   +1 more source