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Number of items: 10.

A

Abdalrahman, Ghada and Lai, Sai Hin and Kumar, Pavitra and Ahmed, Ali Najah and Sherif, Mohsen and Sefelnasr, Ahmed and Chau, Kwok Wing and Elshafie, Ahmed (2022) Modeling the infiltration rate of wastewater infiltration basins considering water quality parameters using different artificial neural network techniques. Engineering Applications of Computational Fluid Mechanics, 16 (1). pp. 397-421. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2021.2019126.

Afan, Haitham Abdulmohsin and Osman, Ahmedbahaaaldin Ibrahem Ahmed and Essam, Yusuf and Ahmed, Ali Najah and Huang, Yuk Feng and Kisi, Ozgur and Sherif, Mohsen and Sefelnasr, Ahmed and Chau, Kwok-wing and El-Shafie, Ahmed (2021) Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques. Engineering Applications of Computational Fluid Mechanics, 15 (1). pp. 1420-1439. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2021.1974093.

Ahmed, Ali Najah and Yafouz, Ayman and Birima, Ahmed H. and Kisi, Ozgur and Huang, Yuk Feng and Sherif, Mohsen and Sefelnasr, Ahmed and El-Shafie, Ahmed (2022) Water level prediction using various machine learning algorithms: A case study of Durian Tunggal river, Malaysia. Engineering Applications of Computational Fluid Mechanics, 16 (1). pp. 422-440. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2021.2019128.

AlDahoul, Nouar and Ahmed, Ali Najah and Allawi, Mohammed Falah and Sherif, Mohsen and Sefelnasr, Ahmed and Chau, Kwok-wing and El-Shafie, Ahmed (2022) A comparison of machine learning models for suspended sediment load classification. Engineering Applications of Computational Fluid Mechanics, 16 (1). pp. 1211-1232. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2022.2073565.

E

Essam, Yusuf and Ahmed, Ali Najah and Ramli, Rohaini and Chau, Kwok-Wing and Ibrahim, Muhammad Shazril Idris and Sherif, Mohsen and Sefelnasr, Ahmed and El-Shafie, Ahmed (2022) Investigating photovoltaic solar power output forecasting using machine learning algorithms. Engineering Applications of Computational Fluid Mechanics, 16 (1). pp. 2002-2034. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2022.2126528.

H

Hanoon, Marwah Sattar and Ahmed, Ali Najah and Kumar, Pavitra and Razzaq, Arif and Zaini, Nur'atiah and Huang, Yuk Feng and Sherif, Mohsen and Sefelnasr, Ahmed and Chau, Kwok Wing and El-Shafie, Ahmed (2022) Wind speed prediction over Malaysia using various machine learning models: Potential renewable energy source. Engineering Applications of Computational Fluid Mechanics, 16 (1). pp. 1673-1689. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2022.2103588.

K

Kumar, Pavitra and Lai, Sai Hin and Mohd, Nuruol Syuhadaa and Kamal, Md Rowshon and Ahmed, Ali Najah and Sherif, Mohsen and Sefelnasr, Ahmed and El-Shafie, Ahmed (2021) Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network. Engineering Applications of Computational Fluid Mechanics, 15 (1). pp. 1843-1867. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2021.1990134.

L

Lai, V and Huang, Y. F. and Koo, C. H. and Ahmed, Ali Najah and El-Shafie, Ahmed (2021) Optimization of reservoir operation at Klang Gate Dam utilizing a whale optimization algorithm and a Levy flight and distribution enhancement technique. Engineering Applications of Computational Fluid Mechanics, 15 (1). pp. 1682-1702. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2021.1982777.

O

Othman, Faridah and Alaaeldin, M.E. and Seyam, Mohammed and Ahmed, Ali Najah and Teo, Fang Yenn and Chow, Ming Fai and Afan, Haitham Abdulmohsin and Sherif, Mohsen and Sefelnasr, Ahmed and El-Shafie, Ahmed (2020) Efficient river water quality index prediction considering minimal number of inputs variables. Engineering Applications of Computational Fluid Mechanics, 14 (1). pp. 751-763. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2020.1760942.

Y

Yafouz, Ayman and Ahmed, Ali Najah and Zaini, Nur'atiah and Sherif, Mohsen and Sefelnasr, Ahmed and El-Shafie, Ahmed (2021) Hybrid deep learning model for ozone concentration prediction: Comprehensive evaluation and comparison with various machine and deep learning algorithms. Engineering Applications of Computational Fluid Mechanics, 15 (1). pp. 902-933. ISSN 1994-2060, DOI https://doi.org/10.1080/19942060.2021.1926328.

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