Machine learning models coupled with empirical mode decomposition for simulating monthly and yearly streamflows: a case study of three watersheds in Ontario, Canada
This paper presents a novel approach for enhancing long-term runoff simulations through the integration of empirical mode decomposition (EMD) with four machine learning (ML) models: ensemble, support vector machine (SVM), convolutional neural networks (CNN), and artificial neural networks with backp...
محفوظ في:
| المؤلفون الرئيسيون: | , , , , |
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| التنسيق: | Artigo |
| اللغة: | Inglês |
| منشور في: |
Taylor & Francis Group
2023-12-01
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| سلاسل: | Engineering Applications of Computational Fluid Mechanics |
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://www.tandfonline.com/doi/10.1080/19942060.2023.2242445 |
| الوسوم: |
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