A Bi-GRU-based encoder–decoder framework for multivariate time series forecasting

Balti, Hanen; Ben Abbes, Ali; Farah, Imed Riadh

doi:10.1007/s00500-023-09531-9

Soft Comput

2024

DOI: 10.1007/s00500-023-09531-9

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A Bi-GRU-based encoder–decoder framework for multivariate time series forecasting

Hanen Balti,

Ali Ben Abbes,

Imed Riadh Farah

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2024

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Cited by 3 publications

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Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models

Sibtain,

Li,

et al. 2024

Water Resour Manage

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The exploitation of hydropower provides cleaner, sustainable and cheaper energy contrary to fossil fuels.Therefore, hydropower offers prospects to meet the sustainable development goals of the United Nations.These bene ts motivate this study to develop different models for e cient runoff prediction utilizing multivariate hydro-meteorological data. The techniques employed for this purpose include correlation analysis, time series decomposition, sample entropy (SE), and sequence2sequence (S2S) algorithm with spatio-temporal attention (STAtt). The decomposition techniques include improved complete ensemble empirical mode decomposition with additive noise (ICEEMDAN) and the maxim overlap discrete wavelet transform (MODWT). The ICEEMDAN-STAtt-S2S model reveals the best prediction results over the counterpart hybrid and standalone models in terms of statistical metrics and comparison plots. The surpassed prediction outcomes substantiate the merger of ICEEMDAN and S2S utilizing STAtt for runoff prediction. Moreover, ICEEMDAN-STAtt-S2S offers the potential for reliable prediction of similar applications, including renewable energy, environment monitoring, and energy resources management.

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Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models

Sibtain,

Li,

et al. 2024

Water Resour Manage

View full text Add to dashboard Cite

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Characterizing drought prediction with deep learning: A literature review

Márquez-Grajales,

Villegas-Vega,

Salas-Martínez

et al. 2024

MethodsX

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Multivariable High-Dimension Time-Series Prediction in SIoT via Adaptive Dual-Graph-Attention Encoder-Decoder With Global Bayesian Optimization

Dong,

Kong,

Yan

et al. 2024

IEEE Internet Things J.

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A Bi-GRU-based encoder–decoder framework for multivariate time series forecasting

Cited by 3 publications

References 30 publications

Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models

Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models

Characterizing drought prediction with deep learning: A literature review

Multivariable High-Dimension Time-Series Prediction in SIoT via Adaptive Dual-Graph-Attention Encoder-Decoder With Global Bayesian Optimization

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