Artificial Intelligence Based Modelling of Adsorption Water Desalination System

Hesham Alhumade, Hegazy Rezk, Abdulrahim A. Al-Zahrani, Sharif F. Zaman and Ahmed Askalany
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Hesham Alhumade: Chemical and Materials Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Hegazy Rezk: College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 11911, Saudi Arabia
Abdulrahim A. Al-Zahrani: Chemical and Materials Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Sharif F. Zaman: Chemical and Materials Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Ahmed Askalany: Mechanical Engineering Department, Faculty of Industrial Education, Sohag University, Sohag 82524, Egypt

Mathematics, 2021, vol. 9, issue 14, 1-13

Abstract: The main target of this research work is to model the output performance of adsorption water desalination system (AWDS) in terms of switching and cycle time using artificial intelligence. The output performance of the ADC system is expressed by the specific daily water production (SDWP), the coefficient of performance (COP), and specific cooling power (SCP). A robust Adaptive Network-based Fuzzy Inference System (ANFIS) model of SDWP, COP, and SCP was built using the measured data. To demonstrate the superiority of the suggested ANFIS model, the model results were compared with those achieved by Analysis of Variance (ANOVA) based on the maximum coefficient of determination and minimum error between measured and estimated data in addition to the mean square error (MSE). Applying ANOVA, the average coefficient-of-determination values were 0.8872 and 0.8223, respectively, for training and testing. These values are increased to 1.0 and 0.9673, respectively, for training and testing thanks to ANFIS based modeling. In addition, ANFIS modelling decreased the RMSE value of all datasets by 83% compared with ANOVA. In sum, the main findings confirmed the superiority of ANFIS modeling of the output performance of adsorption water desalination system compared with ANOVA.

Keywords: artificial intelligence; modelling based ANFIS; adsorption desalination (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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