Title: Estimating household electricity consumption by environmental consciousness

Authors: Ali Azadeh; Ali Narimani; Tayebeh Nazari

Addresses: School of Industrial Engineering and Center of Excellence for Intelligent Based Experimental Mechanics, College of Engineering, University of Tehran, 11365, Iran ' School of Industrial Engineering and Center of Excellence for Intelligent Based Experimental Mechanics, College of Engineering, University of Tehran, 11365, Iran ' School of Industrial Engineering and Center of Excellence for Intelligent Based Experimental Mechanics, College of Engineering, University of Tehran, 11365, Iran

Abstract: It is difficult to model household electricity consumption by considering environmental consciousness through conventional methods. This paper presents a flexible framework based on artificial neural network (ANN), multi-layer perception (MLP), conventional regression and design of experiment (DOE) for estimating household electricity consumption by considering environmental consciousness. Environmental consciousness is evaluated through standard questionnaire. Moreover, DOE is based on analysis of variance (ANOVA) and Duncan multiple range test (DMRT). Furthermore, actual data is compared with ANN MLP and conventional regression model through ANOVA. The significance of this study is the integration of ANN, conventional regression and DOE for flexible and improved modelling of household electricity consumption by incorporating environmental consciousness indicators.

Keywords: household electricity consumption; environmental consciousness; artificial neural networks; ANNs; regression; design of experiments; DOE; analysis of variance; ANOVA; minimum absolute percentage error; MAPE; consumption modelling.

DOI: 10.1504/IJPQM.2015.065983

International Journal of Productivity and Quality Management, 2015 Vol.15 No.1, pp.1 - 19

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 06 Nov 2014 *

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