Estimating household electricity consumption by environmental consciousness

Ali Azadeh, Ali Narimani and Tayebeh Nazari

International Journal of Productivity and Quality Management, 2015, vol. 15, issue 1, 1-19

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. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.inderscience.com/link.php?id=65983 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:15:y:2015:i:1:p:1-19

Access Statistics for this article

More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().