Hybrid Iterative and Tree-Based Machine Learning Algorithms for Lake Water Level Forecasting

Fijani, Elham; Khosravi, Khabat

doi:10.1007/s11269-023-03613-x

Water Resour Manage

2023

DOI: 10.1007/s11269-023-03613-x

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Hybrid Iterative and Tree-Based Machine Learning Algorithms for Lake Water Level Forecasting

Elham Fijani,

Khabat Khosravi

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2024

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Cited by 5 publications

References 62 publications

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A Comparative Assessment of Decision Tree Algorithms for Index of Sediment Connectivity Modelling

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Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models

Sibtain,

Li,

et al. 2024

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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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Enhancing Rock Fragmentation in Mining: Leveraging Ensemble Classification Machine Learning Algorithms for Blast Toe Volume Assessment

Taiwo,

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J. Inst. Eng. India Ser. D

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Hybrid Iterative and Tree-Based Machine Learning Algorithms for Lake Water Level Forecasting

Cited by 5 publications

References 62 publications

A Comparative Assessment of Decision Tree Algorithms for Index of Sediment Connectivity Modelling

A Comparative Assessment of Decision Tree Algorithms for Index of Sediment Connectivity Modelling

Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models

Enhancing Rock Fragmentation in Mining: Leveraging Ensemble Classification Machine Learning Algorithms for Blast Toe Volume Assessment

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