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.
Highlights
It has become evident that the energy and water dilemmas are escalating day by day to the point where they threaten the lives of many people and fuel conflicts between societies [1]
The strength of adsorption desalination systems is that they are suitable for being run with solar energy or waste energy, but they have a weak point, which is their low productivity compared to widespread systems such as reverse osmosis systems (RO) [4]
Compared with Analysis of Variance (ANOVA), the average RMSE value based on all datasets is decreased from 8.607 (ANOVA) to 1.46 by using Adaptive Network-based Fuzzy Inference System (ANFIS)
Summary
It has become evident that the energy and water dilemmas are escalating day by day to the point where they threaten the lives of many people and fuel conflicts between societies [1]. The researchers have improved in this way and made a great effort until they presented many ideas that can be built upon and developed Among these ideas was the idea to use the phenomenon of adsorption to desalinate water with solar energy or waste energy. Desalinated water of 191.3 kg/h has been reached at a heating temperature of 80 ◦ C Another optimization study has been presented by Rezk et al [12] using a model optimization method to declare the optimal operating conditions of solar-driven AD cycle. 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 an Adaptive Network-based Fuzzy.
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