Novel hybrid and weighted ensemble models to predict river discharge series with outliers
In this study, a novel hybrid framework named HVK/HVA-HEM was designed to predict river discharge with outliers. Firstly, the Hampel filter (HF) identifies and corrects outliers in the discharge series. Next, this series was denoised and decomposed using ensemble empirical mode decomposition (EEMD)...
Saved in:
| Main Authors: | Maha Shabbir, Sohail Chand, Farhat Iqbal |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-04-01
|
| Series: | Kuwait Journal of Science |
| Subjects: | |
| Online Access: | https://www.sciencedirect.com/science/article/pii/S2307410824000130 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Outlier Ensemble Based on Isolation Forest: The CBOEA Approach
by: Chaabouni Ali, et al.
Published: (2025-02-01) -
Assessing the stability of indoor farming systems using data outlier detection
by: Jean Pompeo, et al.
Published: (2025-03-01) -
Outlier Detection and Explanation Method Based on FOLOF Algorithm
by: Lei Bai, et al.
Published: (2025-05-01) -
Siting Considerations for Satellite Observation of River Discharge
by: Jack Eggleston, et al.
Published: (2024-06-01) -
Fast Ways to Detect Outliers
by: Emad Obaid Merza, et al.
Published: (2021-03-01)