Analysis of electricity bills using visual continuous maps

作者：Moran A^*; Fuertes J J; Dominguez M; Prada M A; Alonso S; Barrientos P

来源：Neural Computing & Applications, 2013, 23(3-4): 645-655.

DOI：10.1007/s00521-013-1409-8

• Dimensionality reduction
• Neural networks
• Electricity consumption
• Data visualization

The information from the electricity bills of an institution such as the University of Len, with several billing points, constitutes a high-dimensional data set which is quite complicated to visualize at a glance. The use of techniques for dimensionality reduction enables to obtain a two-dimensional representation of the original data set which highlights main features in data and is easier to visualize. If these techniques are combined with interpolation methods, the resulting continuous maps allow comparison and interpretation of a whole range of possible electric data sets, not only the original one. These tools allow us to generate interactive maps that can be used by untrained people to exploit and analyze the information in electricity bills, detect penalties due to a power demand excess or power factor decrease, and make decisions with regard to electricity contracts.

• 出版日期2013-9