Using Singular Spectrum Analysis and Empirical Mode Decomposition to Enhance the Accuracy of a Machine Learning-Based Soil Moisture Forecasting Algorithm-Reference-Cited by-同舟云学术

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Using Singular Spectrum Analysis and Empirical Mode Decomposition to Enhance the Accuracy of a Machine Learning-Based Soil Moisture Forecasting Algorithm

Published:2023 Issue: Volume: Page:
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Author:

Murcia Eduart,Guzmán Sandra M.

Publisher

Elsevier BV

Reference76 articles.

1. Machine learning for predicting field soil moisture using soil, crop, and nearby weather station data in the red river valley of the north;U Acharya;Soil Systems,2021

2. Sub-monthly prediction of harmful algal blooms based on automated cell imaging;V Agarwal;Harmful Algae,2023

3. Artificial intelligence modelling integrated with singular spectral analysis and seasonaltrend decomposition using loess approaches for streamflow predictions;T Akiba;Journal of Hydrology,2019

4. Hankel-based unsupervised anomaly detection;K Bekiroglu;American Control Conference (ACC),2020

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