Search Results - "Encoder-Decoder ConvLSTM"

Coupled Encoder-Decoder ConvLSTM Structure for the Parameter Identification Problems of Time-Dependent Partial Differential Equations

Source: Advances in Applied Mathematics. 14:341-355

An Optimized Model With Encoder-Decoder ConvLSTM for Global Ionospheric Forecasting

Authors: Cheng Wang Kaiyu Xue Chuang Shi

Source: IEEE Geoscience and Remote Sensing Letters. 22:1-5

Encoder–Decoder ConvLSTM Structure with Skip Connections for Solving Time-Dependent Partial Differential Equation

Authors: Qi Guo Jiangtao Xin Hongen Jia et al.

Source: International Journal of Computational Methods.

Forecasting Stock Market Using Machine Learning Approach Encoder-Decoder ConvLSTM

Authors: Khurum Iqbal Ali Hassan Syed Shah Mir Ul Hassan et al.

Source: 2021 International Conference on Frontiers of Information Technology (FIT). :43-48

Subject Terms: 05 social sciences, 0507 social and economic geography

An encoder-decoder ConvLSTM surrogate model for simulating geological CO2 sequestration with dynamic well controls

Authors: Zhao Feng Zeeshan Tariq Xianda Shen et al.

Contributors: Zhao Feng Zeeshan Tariq Xianda Shen et al.

Source: Gas Science and Engineering. 125:205314

File Description: application/pdf

Structural Surrogate Model and Dynamic Response Prediction with Consideration of Temporal and Spatial Evolution: An Encoder–Decoder ConvLSTM Network

Authors: Hong Peng Yaozhi Luo Jingwen Yan et al.

Source: International Journal of Structural Stability and Dynamics. 21:2150140

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology, 0201 civil engineering

Access URL: https://www.worldscientific.com/doi/abs/10.1142/S0219455421501406

An encoder-decoder ConvLSTM surrogate model for simulating geological CO2 sequestration with dynamic well controls.

Authors: Feng, Zhao Tariq, Zeeshan Shen, Xianda et al.

Source: Gas Science & Engineering. May2024, Vol. 125, pN.PAG-N.PAG. 1p.

Subject Terms: Geological carbon sequestration, Spatial analysis (Statistics), Deep learning

PDED-ConvLSTM: Pyramid Dilated Deeper Encoder–Decoder Convolutional LSTM for Arctic Sea Ice Concentration Prediction

Authors: Deyu Zhang Changying Wang Baoxiang Huang et al.

Source: Applied Sciences, Vol 14, Iss 8, p 3278 (2024)

Subject Terms: deep learning, sea ice concentration prediction, pyramidal convolution, dilated encoder–decoder ConvLSTM, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Relation: https://www.mdpi.com/2076-3417/14/8/3278; https://doaj.org/toc/2076-3417; https://doaj.org/article/299eaa279c644087970737e9a35260a4

Availability: https://doi.org/10.3390/app14083278
https://doaj.org/article/299eaa279c644087970737e9a35260a4

Structural Surrogate Model and Dynamic Response Prediction with Consideration of Temporal and Spatial Evolution: An Encoder–Decoder ConvLSTM Network.

Authors: Peng, Hong Yan, Jingwen Yu, Ying et al.

Source: International Journal of Structural Stability & Dynamics; Aug2021, Vol. 21 Issue 10, p1-30, 30p

Subject Terms: STRUCTURAL models, DEEP learning, DYNAMIC models, ARTIFICIAL intelligence, DYNAMIC loads, FORECASTING, SHEAR walls

Multi-Scale Attention and Encoder-Decoder Network for Video Saliency Object Detection.

Authors: Bi, Hongbo Zhu, Huihui Yang, Lina et al.

Source: Pattern Recognition & Image Analysis; Jun2022, Vol. 32 Issue 2, p340-350, 11p

An advanced spatio-temporal convolutional recurrent neural network for storm surge predictions.

Authors: Adeli, Ehsan Sun, Luning Wang, Jianxun et al.

Source: Neural Computing & Applications; Sep2023, Vol. 35 Issue 26, p18971-18987, 17p

Subject Terms: CONVOLUTIONAL neural networks, RECURRENT neural networks, STORM surges, ARTIFICIAL neural networks, EMULATION software, DATABASES, COMPUTATIONAL fluid dynamics

Advancing spatiotemporal forecasts of CO[formula omitted] plume migration using deep learning networks with transfer learning and interpretation analysis.

Authors: Fan, Ming Wang, Hongsheng Zhang, Jing et al.

Source: International Journal of Greenhouse Gas Control. Feb2024, Vol. 132, pN.PAG-N.PAG. 1p.

Subject Terms: Deep learning, Transfer of training, Forecasting, Carbon dioxide, Job performance, Prediction models

Ionospheric TEC Forecasting with ED-ConvLSTM-Res Integrating Multi-Channel Features.

Authors: Yang, Jiayue Huang, Wengeng Zhang, Lei et al.

Source: Remote Sensing; Nov2025, Vol. 17 Issue 21, p3564, 14p

Subject Terms: SOLAR activity, FORECASTING, IONOSPHERIC electron density, SPATIOTEMPORAL processes, GEOMAGNETIC variations, MACHINE learning

Global Ionosphere Total Electron Content Prediction Based on Bidirectional Denoising Wavelet Transform Convolution.

Authors: Sun, Liwei Yuan, Guoming Le, Huijun et al.

Source: Atmosphere; Oct2025, Vol. 16 Issue 10, p1139, 21p

Subject Terms: IONOSPHERE, TOTAL electron content (Atmosphere), CONVOLUTIONAL neural networks, SPATIOTEMPORAL processes, MACHINE learning, WAVELET transforms

MS Mamba: Spectrum Forecasting Method Based on Enhanced Mamba Architecture.

Authors: Liu, Dingyin Xu, Donghui Hu, Guojie et al.

Source: Electronics (2079-9292); Sep2025, Vol. 14 Issue 18, p3708, 17p

Subject Terms: COGNITIVE radio, SPATIOTEMPORAL processes, MULTIUSER channels, STATE-space methods, MATHEMATICAL optimization, SOFTWARE architecture, HYPOTHESIS

A Convolutional Neural Networks Model Based on Wavelet Packet Transform for Enhanced Earthquake Early Warning.

Authors: Wang, Huiwei Xu, Longhe Xie, Xingsi

Source: International Journal of Structural Stability & Dynamics; 7/15/2025, Vol. 25 Issue 13, p1-26, 26p

Subject Terms: CONVOLUTIONAL neural networks, WAVELET transforms, EARTHQUAKES, WAVELETS (Mathematics)

Optimized feature selection based on machine learning models for robust stock market prediction.

Authors: Daoud, Mouna Ben Hamdi, Manel Younes, Rabeb et al.

Source: International Journal of Innovative Research & Scientific Studies; 2025, Vol. 8 Issue 3, p5086-5099, 14p

Subject Terms: MACHINE learning, FEATURE selection, ARTIFICIAL intelligence, STANDARD & Poor's 500 Index, RANDOM forest algorithms

An advanced spatio-temporal convolutional recurrent neural network for storm surge predictions

Authors: Adeli, Ehsan Sun, Luning Wang, Jianxun et al.

Index Terms: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computational Engineering, Finance, and Science, text

URL: http://arxiv.org/abs/2204.09501

Identification and Prediction of Casing Collar Signal Based on CNN-LSTM.

Authors: Jing, Jun Qin, Yiman Zhu, Xiaohua et al.

Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ); Apr2025, Vol. 50 Issue 7, p4897-4911, 15p

Subject Terms: LONG short-term memory, CONVOLUTIONAL neural networks, BATHYMETRY, STATISTICAL correlation, DEEP learning, SIMULATION methods & models

A New and Tested Ionospheric TEC Prediction Method Based on SegED-ConvLSTM.

Authors: Liu, Yuanhang Gong, Yingkui Zhang, Hao et al.

Source: Remote Sensing; Mar2025, Vol. 17 Issue 5, p885-1, 26p

Subject Terms: LONG short-term memory, GLOBAL Positioning System, STANDARD deviations, SPACE environment, CONVOLUTIONAL neural networks