Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm
Notes or commentaries
Karbasi, Masoud, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Jamei, Mehdi, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2024. "Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm." Scientific Reports. 14 (1). https://doi.org/10.1038/s41598-024-69309-3
Article Title | Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm |
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ERA Journal ID | 201487 |
Article Category | Notes or commentaries |
Authors | Karbasi, Masoud, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Jamei, Mehdi, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher |
Journal Title | Scientific Reports |
Journal Citation | 14 (1) |
Article Number | 14 |
Number of Pages | 1 |
Year | 2024 |
Publisher | Nature Publishing Group |
Place of Publication | United Kingdom |
ISSN | 2045-2322 |
Digital Object Identifier (DOI) | https://doi.org/10.1038/s41598-024-69309-3 |
Web Address (URL) | https://www.nature.com/articles/s41598-024-69309-3 |
Abstract | Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-024-65837-0, published online 01 July 2024 In the original version of this Article, Changhyun Jun and Aitazaz Ahsan Farooque were omitted as corresponding authors. The correct corresponding authors for this Article are Masoud Karbasi, Changhyun Jun and Aitazaz Ahsan Farooque. The original Article has been corrected. © The Author(s) 2024. |
Related Output | |
Is supplement to | Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm |
Contains Sensitive Content | Does not contain sensitive content |
Public Notes | This is a corrected version of the publication. |
Byline Affiliations | University of Zanjan, Iran |
UniSQ College | |
University of Hawaii, United States | |
Chung-Ang University, Korea | |
Shahid Chamran University of Ahvaz, Iran | |
Al-Ayen University, Iraq | |
University of Prince Edward Island, Canada | |
King Fahd University of Petroleum and Minerals, Saudi Arabia |
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