Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System
The performance of a hybrid solar desalination system is predicted in this work using an enhanced prediction method based on a supervised machine-learning algorithm. A humidification–dehumidification (HDH) unit and a single-stage flashing evaporation (SSF) unit make up the hybrid solar desalination...
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| Format: | Article |
| Language: | English |
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2023-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/3/1185 |
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| author | Abdelhameed Ibrahim El-Sayed M. El-kenawy A. E. Kabeel Faten Khalid Karim Marwa M. Eid Abdelaziz A. Abdelhamid Sayed A. Ward Emad M. S. El-Said M. El-Said Doaa Sami Khafaga |
| author_facet | Abdelhameed Ibrahim El-Sayed M. El-kenawy A. E. Kabeel Faten Khalid Karim Marwa M. Eid Abdelaziz A. Abdelhamid Sayed A. Ward Emad M. S. El-Said M. El-Said Doaa Sami Khafaga |
| author_sort | Abdelhameed Ibrahim |
| collection | DOAJ |
| description | The performance of a hybrid solar desalination system is predicted in this work using an enhanced prediction method based on a supervised machine-learning algorithm. A humidification–dehumidification (HDH) unit and a single-stage flashing evaporation (SSF) unit make up the hybrid solar desalination system. The Al-Biruni Earth Radius (BER) and Particle Swarm Optimization (PSO) algorithms serve as the foundation for the suggested algorithm. Using experimental data, the BER–PSO algorithm is trained and evaluated. The cold fluid and injected air volume flow rates were the algorithms’ inputs, and their outputs were the hot and cold fluids’ outlet temperatures as well as the pressure drop across the heat exchanger. Both the volume mass flow rate of hot fluid and the input temperatures of hot and cold fluids are regarded as constants. The results obtained show the great ability of the proposed BER–PSO method to identify the nonlinear link between operating circumstances and process responses. In addition, compared to the other analyzed models, it offers better statistical performance measures for the prediction of the outlet temperature of hot and cold fluids and pressure drop values. |
| first_indexed | 2024-03-11T09:46:07Z |
| format | Article |
| id | doaj.art-89a90e614efd498380b685ca02716ef9 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T09:46:07Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-89a90e614efd498380b685ca02716ef92023-11-16T16:33:53ZengMDPI AGEnergies1996-10732023-01-01163118510.3390/en16031185Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination SystemAbdelhameed Ibrahim0El-Sayed M. El-kenawy1A. E. Kabeel2Faten Khalid Karim3Marwa M. Eid4Abdelaziz A. Abdelhamid5Sayed A. Ward6Emad M. S. El-Said7M. El-Said8Doaa Sami Khafaga9Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura 35516, EgyptDepartment of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, EgyptFaculty of Engineering, Delta University for Science and Technology, Gamasa 35712, EgyptDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaFaculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura 35712, EgyptDepartment of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra 11961, Saudi ArabiaFaculty of Engineering, Delta University for Science and Technology, Gamasa 35712, EgyptMechanical Engineering Department, Faculty of Engineering, Dameitta University, Damietta 34511, EgyptElectrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, EgyptDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaThe performance of a hybrid solar desalination system is predicted in this work using an enhanced prediction method based on a supervised machine-learning algorithm. A humidification–dehumidification (HDH) unit and a single-stage flashing evaporation (SSF) unit make up the hybrid solar desalination system. The Al-Biruni Earth Radius (BER) and Particle Swarm Optimization (PSO) algorithms serve as the foundation for the suggested algorithm. Using experimental data, the BER–PSO algorithm is trained and evaluated. The cold fluid and injected air volume flow rates were the algorithms’ inputs, and their outputs were the hot and cold fluids’ outlet temperatures as well as the pressure drop across the heat exchanger. Both the volume mass flow rate of hot fluid and the input temperatures of hot and cold fluids are regarded as constants. The results obtained show the great ability of the proposed BER–PSO method to identify the nonlinear link between operating circumstances and process responses. In addition, compared to the other analyzed models, it offers better statistical performance measures for the prediction of the outlet temperature of hot and cold fluids and pressure drop values.https://www.mdpi.com/1996-1073/16/3/1185humidification–dehumidificationflashing desalinationmachine learningmeta-heuristic optimization |
| spellingShingle | Abdelhameed Ibrahim El-Sayed M. El-kenawy A. E. Kabeel Faten Khalid Karim Marwa M. Eid Abdelaziz A. Abdelhamid Sayed A. Ward Emad M. S. El-Said M. El-Said Doaa Sami Khafaga Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System Energies humidification–dehumidification flashing desalination machine learning meta-heuristic optimization |
| title | Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System |
| title_full | Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System |
| title_fullStr | Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System |
| title_full_unstemmed | Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System |
| title_short | Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System |
| title_sort | al biruni earth radius optimization based algorithm for improving prediction of hybrid solar desalination system |
| topic | humidification–dehumidification flashing desalination machine learning meta-heuristic optimization |
| url | https://www.mdpi.com/1996-1073/16/3/1185 |
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