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Water 2017, 9(7), 492; https://doi.org/10.3390/w9070492

Factor Analysis and Estimation Model of Water Consumption of Government Institutions in Taiwan

1
Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology (YunTech), 123, University Rd., Sec. 3, Douliou City, Yunlin County 64002, Taiwan
2
Heng-Zhi Technology Company Ltd., 7-3, Minsheng Rd., Madou District, Tainan City 72145, Taiwan
3
Department of Tourism and Leisure, National Penghu University of Science and Technology, No. 300, Liuhe Rd., Magong City, Penghu County 880, Taiwan
4
Department and Graduate School of Safety, Health, and Environmental Engineering, YunTech, 123, University Rd., Sec. 3, Douliou City, Yunlin County 64002, Taiwan
*
Author to whom correspondence should be addressed.
Received: 8 April 2017 / Revised: 24 June 2017 / Accepted: 3 July 2017 / Published: 5 July 2017
(This article belongs to the Special Issue Modeling of Water Systems)
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Abstract

Models for adequately estimating water consumption in Taiwanese government institutions were developed to assist the government to more accurately predict and account for their water needs. A correlation coefficient matrix of associated factors was constructed based on records per unit of water consumption, describing the impact of various water consumption factors. To understand and quantify the effect of the impact factors, linear and nonlinear regression models, as well as an artificial neural network model were adopted. To account for data variability, the data used for modelling were either fully or partially adopted. For partial adoption, the quartile method was employed to remove any outliers. Analysis of the factors affecting water consumption revealed that the building floor area and number of personnel in an organization had the largest impact on estimated consumption, followed by the number of residential personnel. As the coefficient of variation for the green irrigated area and number of consulting personnel was low, the total area and the total number personnel of water consumption decreased the effectiveness of the model. View Full-Text
Keywords: artificial neural network; outlier; quartile outlier method; statistical analysis; water consumption artificial neural network; outlier; quartile outlier method; statistical analysis; water consumption
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Huang, A.-C.; Lee, T.-Y.; Lin, Y.-C.; Huang, C.-F.; Shu, C.-M. Factor Analysis and Estimation Model of Water Consumption of Government Institutions in Taiwan. Water 2017, 9, 492.

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