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Estimating household electricity consumption by environmental consciousness

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  • Ali Azadeh
  • Ali Narimani
  • Tayebeh Nazari

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.

Suggested Citation

  • Ali Azadeh & Ali Narimani & Tayebeh Nazari, 2015. "Estimating household electricity consumption by environmental consciousness," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 15(1), pages 1-19.
    • Handle: RePEc:ids:ijpqma:v:15:y:2015:i:1:p:1-19
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    Cited by:

    1. Madeline Hui Li Lee & Yee Chee Ser & Ganeshsree Selvachandran & Pham Huy Thong & Le Cuong & Le Hoang Son & Nguyen Trung Tuan & Vassilis C. Gerogiannis, 2022. "A Comparative Study of Forecasting Electricity Consumption Using Machine Learning Models," Mathematics, MDPI, vol. 10(8), pages 1-23, April.

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