%0 Journal Article
	%A Abdel Hamid Ajbar and  Emad Ali
	%D 2012
	%J International Journal of Geological and Environmental Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 65, 2012
	%T Water Demand Prediction for Touristic Mecca City in Saudi Arabia using Neural Networks
	%U https://publications.waset.org/pdf/4943
	%V 65
	%X Saudi Arabia is an arid country which depends on
costly desalination plants to satisfy the growing residential water
demand. Prediction of water demand is usually a challenging task
because the forecast model should consider variations in economic
progress, climate conditions and population growth. The task is
further complicated knowing that Mecca city is visited regularly by
large numbers during specific months in the year due to religious
occasions. In this paper, a neural networks model is proposed to
handle the prediction of the monthly and yearly water demand for
Mecca city, Saudi Arabia. The proposed model will be developed
based on historic records of water production and estimated visitors-
distribution. The driving variables for the model include annuallyvarying
variables such as household income, household density, and
city population, and monthly-varying variables such as expected
number of visitors each month and maximum monthly temperature.
	%P 231 - 235