Analysis of Data Cleaning Techniques for Electrical Energy Consumption of a Public Building

Statistical Techniques and Artificial Intelligence
are becoming much more a necessity in a fastened world rather
than just a theoretical use case. In order to satisfy this need, the
optimization process starts with data collecting and cleaning.
The aim of this paper is to provide a short overview of the outlier
detection methods and to explain the need for data cleaning in
the field of energy consumption by analyzing the energetic
profile data from the Technical University of Cluj-Napoca’s
swimming complex. In the first and second parts of the article,
a short overview of cleaning methods are presented. The third
part compares the efficiency of the proposed methods. Finally,
but not least the fourth part of the article is dedicated to
conclusions and future work.