Results 131 to 140 of about 13,592 (226)
Advanced Theory and Simulations, Volume 9, Issue 8, August 2026.A novel adaptive weighted ensemble framework integrating BiGRU, enhanced attention‐based TCN, and linear regression improves one‐hour‐ahead PM10 forecasting by jointly capturing sequential dependencies, multi‐scale temporal patterns, and residual linear relationships.
Huseyin Cagan Kilinc +4 more
wiley +1 more source
Development and evaluation of bidirectional LSTM freeway traffic forecasting models using simulation data. [PDF]
Sci Rep, 2021 Abduljabbar RL, Dia H, Tsai PW.
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, Volume 2, Issue 4, August 2026.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Spatial feature recognition and layout method based on improved CenterNet and LSTM frameworks
ETRI JournalExisting spatial feature recognition and layout methods primarily identify spatial components manually, which is time-consuming and inefficient, and the constraint relationship between objects in space can be difficult to observe.
Yuxuan Gu +4 more
doaj +1 more source
Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic. [PDF]
Neurocomputing (Amst), 2022 Quilodrán-Casas C +5 more
europepmc +1 more source
Advanced Intelligent Systems, Volume 8, Issue 8, August 2026.A hybrid quantum‐classical architecture is introduced to accurately identify dynamical quantum phase transitions from time‐evolved quantum states. The QCNN serves as a quantum dynamical feature extractor, while the classical network learns temporal correlations from a low‐dimensional readout sequence. The framework attains high accuracy, remains robust
Daili Li +3 more
wiley +1 more source
Predicting COVID-19 cases using bidirectional LSTM on multivariate time series. [PDF]
Environ Sci Pollut Res Int, 2021 Said AB, Erradi A, Aly HA, Mohamed A.
europepmc +1 more source
Image Captioning by Using Bidirectional Lstm Neural Network
Abstract Putting captions on images is an important phase in image processing and machine vision which divides an image into different regions. In the related captioning operation, similar attributes are extracted from each region and a single caption is opted for the title of the input for the relevant image. In the developed world, due to the
Farnaz Hoseini, Anaram Yaghoobi Notash
openaire +1 more source
A Deep Learning Model for Decadal Indian Ocean Dipole
Atmospheric Science Letters, Volume 27, Issue 8, August 2026.This study develops a deep learning model based on a bidirectional gated recurrent unit (BiGRU) to predict the decadal Indian Ocean Dipole (IOD). Using CMIP6 DCPP models, we first assess IOD predictability, then show the BiGRU model achieves substantially higher skill than traditional dynamical models.
Sitraka Ny Aina Raharivelo +4 more
wiley +1 more source
χ2-BidLSTM: A Feature Driven Intrusion Detection System Based on χ2 Statistical Model and Bidirectional LSTM. [PDF]
Sensors (Basel), 2022 Imrana Y +6 more
europepmc +1 more source