Log logistic distribution to model water demand data
Surendran, Seevali and Tota-Maharaj, Kiran (2015) Log logistic distribution to model water demand data. Procedia Engineering, 119. pp. 798-802. ISSN 1877-7058 (doi:https://doi.org/10.1016/j.proeng.2015.08.940)
|
PDF (Available online 1 September 2015 under a Creative Commons License (http://creativecommons.org/licenses/by-nc-nd/4.0/))
13864_TOTA_MAHARAJ_Procedia_Engineering_(OPEN_ACCESS_Available_online_1_September_2015).pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (356kB) |
Abstract
There had been insufficient studies previously to conclude the suitability of the appropriate probability distribution functions in modelling water demand. The purpose of this study is to find an appropriate probability density function to apply in simulating water demand using real water consumption data. Daily water consumption data for four years obtained from a water company in UK and analysed using normal, log normal, log logistic and Weibull distributions and a comparison on the applicability of each distribution was assessed. Statistical modelling was performed using MINITAB. The Anderson Darling (AD) statistic was used as the goodness of fit parameter in the analysis.
Item Type: | Article |
---|---|
Additional Information: | [1] Open Access publication. Available online 1 September 2015 under a Creative Commons License (http://creativecommons.org/licenses/by-nc-nd/4.0/). [2] Published in Procedia Engineering, Volume 119, 2015 - Computing and Control for the Water Industry (CCWI2015) Sharing the best practice in water management. Edited by Bogumil Ulanicki, Zoran Kapelan and Joby Boxall. |
Uncontrolled Keywords: | water demand, stochastic nature, probability distribution function, log logistic distribution, Minitab, Anderson Darling |
Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences T Technology > TA Engineering (General). Civil engineering (General) |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science |
Related URLs: | |
Last Modified: | 15 Oct 2016 07:28 |
URI: | http://gala.gre.ac.uk/id/eprint/13864 |
Actions (login required)
View Item |
Downloads
Downloads per month over past year