Novel hybrid and weighted ensemble models to predict river discharge series with outliers-Reference-Cited by-同舟云学术

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Novel hybrid and weighted ensemble models to predict river discharge series with outliers

Published:2024-04 Issue:2 Volume:51 Page:100188
ISSN:2307-4108
Container-title:Kuwait Journal of Science
language:en
Short-container-title:Kuwait Journal of Science

Author:

Shabbir Maha^ORCID,Chand Sohail^ORCID,Iqbal Farhat^ORCID

Publisher

Elsevier BV

Reference20 articles.

1. A two-stage multiple-point conceptual model to predict river stage-discharge process using machine learning approaches;Alizadeh;J. Water Climate Change,2021

2. Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool;Aqil;J. Environ. Manag.,2007

3. A hybrid model to predict Monthly streamflow using neighboring rivers Annual flows;Al-Juboori;Water Resour. Manag.,2021

4. Forecasting daily river flows using nonlinear time series models;Amiri;J. Hydrol.,2015

5. Nearest neighbor pattern classification;Cover;IEEE Trans. Inf.,1967

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel hybrid approach based on outlier and error correction methods to predict river discharge using meteorological variables;Environmental and Ecological Statistics;2024-07-23

2. A novel hybrid framework to model the relationship of daily river discharge with meteorological variables;Meteorology Hydrology and Water Management;2024-05-06

3. Hybrid Approach for Streamflow Prediction: LASSO-Hampel Filter Integration with Support Vector Machines, Artificial Neural Networks, and Autoregressive Distributed Lag Models;Water Resources Management;2024-04-18

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