Assessing domestic factors determining water consumption in a semi-arid area (Sedrata City) using artificial neural networks and principal component analysis

Journal of Water and Land Development

article

Menal Zeroual¹  Azzedine Hani¹  Amir Boustila² 

[1] University of Badji Mokhtar, Faculty of Earth Sciences, Laboratory of water resource and sustainable development;University of Badji Mokhtar, Faculty of Earth Sciences, Laboratory of natural resource and development

关键词: artificial neural networks;    domestic water use determinants;    household water consumption;    principal component analysis;    semi-arid area;   

DOI  :  10.24425/jwld.2021.137115

学科分类：农业科学（综合）

来源: Instytut Technologiczno-Przyrodniczego / Institute of Technology and Life Sciences

【 摘 要 】

The growing demand for fresh water and its scarcity are the major problems encountered in semi-arid cities. Two different techniques have been used to assess the main determinants of domestic water in the Sedrata City, North-East Algeria: prin-cipal component analysis (PCA) and artificial neural networks (ANNs). To create the ANNs models based on the PCA, twelve explanatory variables are initially investigated, of which nine are socio-economic parameters and three physical char-acteristics of building units. Two optimum ANNs models have been selected where correlation coefficients equal to 0.99 in training, testing and validation phases. In addition, results demonstrate that the combination of socio-economic parameters with physical characteristics of building units enhances the assessment of household water consumption.

【 授权许可】

Unknown