Applications of machine learning techniques in performance evaluation of solar desalination systems – a concise review

Rashidi, Saman, Karimi, Nader and Yan, Wei-Mon (2022) Applications of machine learning techniques in performance evaluation of solar desalination systems – a concise review. Engineering Analysis with Boundary Elements, 144, 399-408. (doi:10.1016/j.enganabound.2022.08.031).

Abstract

Predictive models of solar desalination systems are of crucial importance for the performance evaluation of the new and existing designs of such systems. To respond to the fast growing needs for accurate and reliable modeling schemes, machine-learning techniques have been developed and utilized. A large number of methods have been applied to desalination systems with varying degrees of success, leading to the formation of a potentially confusing situation about the applicability of different techniques. To resolve this issue, a comprehensive survey of literature on the applications of machine learning techniques in solar desalination systems, is carried out in this study. The development made so far as well as the main challenges facing this approach are discussed and a number of conclusions are reached, followed by several recommendations for future studies. In addition, different machine learning methodologies pertinent to this field are classified and discussed briefly.

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Contributors

Author: Nader Karimi

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