The Effect of Variations in Micro-components of Domestic Water Consumption Data on the Classification of Excessive Water Usage

Autor:	Nur Izzah Jamil, Khairul A. Rasmani, Nor Salyana Mohd Salleh
Rok vydání:	2015
Předmět:	Estimation Consumer data Domestic water consumption Computer science domestic water consumption computer.software_genre Water consumption Task (project management) Micro components Statistical classification classification General Materials Science Data mining computer
Zdroj:	Procedia - Social and Behavioral Sciences. 195:1865-1871
ISSN:	1877-0428
DOI:	10.1016/j.sbspro.2015.06.422
Popis:	Several studies have been conducted to explore the potential of using consumer data for the estimation of domestic water consumption. However, it is not an easy task to collect and record consumer data that precisely represent daily, weekly or monthly household water usage. This paper investigates the effect of variations in water consumption data on the classification of domestic water usage levels. Two datasets were used in this study. The first dataset consists of ten predictive variables related to household water usage. The second dataset was generated based on the first dataset where four generic features were created to represent water consumption based on four categories of activities related to water usage. Selected classification algorithms were used for classification task. The findings show that variations in consumer data have very little effect on classification outcomes suggesting that data collected from consumer suitable to be used for predicting excessive domestic water usage.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5463df7610c0dcc142a7a858f167fbf5 https://doi.org/10.1016/j.sbspro.2015.06.422 Zobrazit plný text záznamu