Výsledky vyhledávání - ConvLSTM encoder-decoder model*

An Optimized Model With Encoder-Decoder ConvLSTM for Global Ionospheric Forecasting Autor Wang, Cheng, Xue, Kaiyu, Shi, Chuang

“… This study introduces two optimized models based on the ConvLSTM cell with an encoder-decoder structure to enhance forecasting performance…”
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Prediction of maize growth stages based on deep learning Autor Yue, Yang, Li, Jin-Hai, Fan, Li-Feng, Zhang, Li-Li, Zhao, Peng-Fei, Zhou, Qiao, Wang, Nan, Wang, Zhong-Yi, Huang, Lan, Dong, Xue-Hui

“…•ConvLSTM encoder-decoder model can forecast daily weather factors correctly.•Hybrid model and data-driven model can predict maize growth stages…”
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ED‐ConvLSTM: A Novel Global Ionospheric Total Electron Content Medium‐Term Forecast Model Autor Xia, Guozhen, Zhang, Fubin, Wang, Cheng, Zhou, Chen

“…In this paper, we proposed an innovative encoder‐decoder structure with a convolution long short‐term memory (ED‐ConvLSTM…”
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Forecasting Stock Market Using Machine Learning Approach Encoder-Decoder ConvLSTM Autor Iqbal, Khurum, Hassan, Ali, Hassan, Syed Shah Mir Ul, Iqbal, Shuaib, Aslam, Faheem, Mughal, Khurrum S

“… The goal of this study is to create a hybrid Deep Learning model (Encoder-Decoder ConvLSTM…”
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PDED-ConvLSTM: Pyramid Dilated Deeper Encoder–Decoder Convolutional LSTM for Arctic Sea Ice Concentration Prediction Autor Zhang, Deyu, Wang, Changying, Huang, Baoxiang, Ren, Jing, Zhao, Junli, Hou, Guojia

“… To address these challenges, we propose an innovative encoder–decoder pyramid dilated convolutional long short-term memory network (DED-ConvLSTM…”
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A multi-embedding neural model for incident video retrieval Autor Chiang, Ting-Hui, Tseng, Yi-Chun, Tseng, Yu-Chee

“… We propose an encoder-decoder ConvLSTM model that explores multiple embeddings of a video to facilitate comparison of similarity between a pair of videos…”
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Advancing spatiotemporal forecasts of CO2 plume migration using deep learning networks with transfer learning and interpretation analysis Autor Fan, Ming, Wang, Hongsheng, Zhang, Jing, Hosseini, Seyyed A., Lu, Dan

“… In this work, we propose two deep learning models, Auto-Encoder (AE)-LSTM and Encoder-Decoder (ED…”
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EDDA-ConvLSTM: Encoder-Decoder Dual Attention ConvLSTM for Moroccan Coastal Sea Surface Temperature Prediction Autor Zahrae El Azhary, Fatima, Minaoui, Khalid

“…This study presents an advanced encoder-decoder dual attention convolutional long short-term memory (ConvLSTM…”
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An advanced spatio-temporal convolutional recurrent neural network for storm surge predictions Autor Adeli, Ehsan, Sun, Luning, Wang, Jianxun, Taflanidis, Alexandros A.

“…In this research paper, we study the capability of artificial neural network models to emulate storm surge based on the storm track/size/intensity history, leveraging a database of synthetic storm simulations…”
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Optimizing hyperparameters of Data-driven simulation-assisted-Physics learned AI (DPAI) model to reduce compounding error Autor Gantala, Thulsiram, Balasubramaniam, Krishnan

“… DPAI model has layers of encoder–decoder structure with modified convolutional long short-term memory (ConvLSTM…”
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Deep unsupervised multi-modal fusion network for detecting driver distraction Autor Zhang, Yuxin, Chen, Yiqiang, Gao, Chenlong

“… It is an end-to-end model composing of three main modules: multi-modal representation learning, multi-scale feature fusion and unsupervised driver distraction detection…”
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Spatiotemporal Prediction of Ionospheric Total Electron Content Based on ED-ConvLSTM Autor Li, Liangchao, Liu, Haijun, Le, Huijun, Yuan, Jing, Shan, Weifeng, Han, Ying, Yuan, Guoming, Cui, Chunjie, Wang, Junling

“… Our ED-ConvLSTM model is built based on the encoder-decoder architecture, which includes two modules…”
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DPAI: A Data-driven simulation-assisted-Physics learned AI model for transient ultrasonic wave propagation Autor Gantala, Thulsiram, Balasubramaniam, Krishnan

“… The DPAI model consists of modified convolutional long short-term memory (ConvLSTM) with an encoder–decoder structure, which learns the representation of spatio-temporal dependence from input sequence data…”
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Detection of Forest Burned Area Using a Spatiotemporal Algorithm Based on Spectral Index Time Series Data Autor Li, Yunhao, Liu, Jinxiu, Maeda, Eduardo Eiji, Li, Xuecao, Pellikka, Petri, Heiskanen, Janne

“… (ConvLSTM) units with a multiscale encoder-decoder architecture to capture both spatial and temporal dependencies inherent in satellite image time series…”
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Prediction of Yangtze River streamflow based on deep learning neural network with El Niño–Southern Oscillation Autor Ha, Si, Liu, Darong, Mu, Lin

“… Current hydrological models based on physical mechanisms can give accurate predictions of streamflow, but the effective prediction period is only about 1 month in advance, which is too short for decision making…”
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Operational Forecasting of Global Ionospheric TEC Maps 1-, 2-, and 3-Day in Advance by ConvLSTM Model Autor Yang, Jiayue, Huang, Wengeng, Xia, Guozhen, Zhou, Chen, Chen, Yanhong

“… The proposed model utilizes an encoder-decoder structure with a Convolution Long Short-Term Memory (ConvLSTM…”
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Energy Demand Load Forecasting for Electric Vehicle Charging Stations Network based on ConvLSTM and BiConvLSTM Architectures Autor Mohammad, Faisal, Kang, Dong-Ki, Ahmed, Mohamed A., Kim, Young-Chon

“…The electrification of transport has proved to be a breakthrough to uplift the sustainable and eco-friendly platform in the global sector in which electric…”
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ED‐AttConvLSTM: An Ionospheric TEC Map Prediction Model Using Adaptive Weighted Spatiotemporal Features Autor Li, Liangchao, Liu, Haijun, Le, Huijun, Yuan, Jing, Wang, Haoran, Chen, Yi, Shan, Weifeng, Ma, Li, Cui, Chunjie

“…‐AttConvLSTM, using a Convolutional Long Short‐Term Memory (ConvLSTM) network and attention mechanism based on encoder‐decoder structure…”
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ConvLSTM Based Temperature Forecast Modification Model for North China Autor Huan-tong, GENG, Zhong-yan, HU, Tian-lei, WANG

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Towards a General Prediction System for the Primary Delay in Urban Railways Autor Wu, Jianqing, Zhou, Luping, Cai, Chen, Dong, Fang, Shen, Jun, Sun, Geng

“… Finally, we demonstrate an advanced deep learning model, the novel ConvLSTM Encoder-Decoder model with CPS for better primary delay predictions…”
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