Abstract
Abstract Water scarcity is one of the world's fastest growing epidemics. Therefore, to combat it or mitigate the risks one must first understand how water is being consumed. This study focuses on the analysis of domestic water consumption with reference to how much of it is being consumed. Additionally, the study aims to propose an applicable and consistent method to forecast urban water consumption by using soft computing techniques. The investigation highlights the hourly, daily and monthly water consumption levels as well as the relationship between climate change and water demand using gene expression programming (GEP). The results of the study are relatively promising as it demonstrates that GEP can predict water consumption incorporating seasonal changes of wet and dry periods.
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