Dataset Open Access

Appliances Energy Dataset

Chang Wei Tan; Christoph Bergmeir; Francois Petitjean; Geoffrey I Webb


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    <subfield code="a">&lt;p&gt;This dataset is part of the Monash, UEA &amp;amp;&amp;nbsp;UCR time series regression repository.&amp;nbsp;&lt;a href="http://tseregression.org/"&gt;http://tseregression.org/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;The goal of this dataset is to predict total energy usage in kWh of a house. This dataset contains 138 time series obtained from the Appliances Energy Prediction dataset from the UCI repository.&amp;nbsp;The time series has 24 dimensions. This includes temperature and humidity measurements of 9 rooms in a house, monitored with a ZigBee wireless sensor network.&amp;nbsp;It also includes weather and climate data such as temperature, pressure, humidity, wind speed, visibility and dewpoint measured from Chievres airport.&amp;nbsp;The data set is averaged for 10 minutes period and spanning 4.5 months.&lt;/p&gt;

&lt;p&gt;Please refer to &lt;a href="https://archive.ics.uci.edu/ml/datasets/Appliances+energy+prediction"&gt;https://archive.ics.uci.edu/ml/datasets/Appliances+energy+prediction&lt;/a&gt;&amp;nbsp; for more details&lt;br&gt;
&lt;br&gt;
Relevant papers&lt;br&gt;
Luis M. Candanedo, Veronique Feldheim, Dominique Deramaix, Data driven prediction models of energy use of appliances in a low-energy house, Energy and Buildings, Volume 140, 1 April 2017, Pages 81-97, ISSN 0378-7788&lt;br&gt;
&lt;br&gt;
Citation request&lt;br&gt;
Luis M. Candanedo, Veronique Feldheim, Dominique Deramaix, Data driven prediction models of energy use of appliances in a low-energy house, Energy and Buildings, Volume 140, 1 April 2017, Pages 81-97, ISSN 0378-7788&lt;/p&gt;</subfield>
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