Hourly Prediction of Building Energy Consumption: An Incremental ANN Approach

Aulon Shabani and Orion Zavalani
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Aulon Shabani: PhD student, Polytechnic University of Tirana, Faculty of electrical Engineering
Orion Zavalani: Professor, Polytechnic University of Tirana, Faculty of electrical Engineering

European Journal of Engineering and Technology Research, 2017, vol. 2, issue 7, 27-32

Abstract: Rapid growth of buildings energy consumption puts the focus to improve energy efficiency by building engineers and operators. Energy management through forecasting approaches using machine-learning algorithms is an increasing research domain. Most of algorithms focus on predicting energy consumption when a considerable amount of past-observed data exist. In this paper, we focus on the case when small amount of available data exist and the amount of data increases incrementally by time. Artificial Neural Networks used as the learning algorithm take as the training data mini batches of different sizes. Algorithm is evaluated on different batch sizes and compared to baseline learner.

Keywords: Energy Prediction; Incremental Learning; Neural Networks; Energy Efficiency (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:2:y:2017:i:7:id:60397

DOI: 10.24018/ejeng.2017.2.7.397

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