IDENTIFICATION OF TYPE DAILY DIAGRAMS OF ELECTRIC CONSUMPTION BASED ON CLUSTER ANALYSIS OF MULTI-DIMENSIONAL DATA BY NEURAL NETWORK
This article establishes a mathematical description of a self-organizing neural network used for cluster analysis with a subsequent sampling of its effectiveness as an example of identification of the type daily diagrams of electric energy-consumption of complex intelligent buildings within an electric micro grid, namely for a typical work day and a day off on the basis of its annual history. The mentioned type daily diagram can be used to predict power consumption. This method is given in the context of the commonly used procedure for cluster analysis. The experiment was processed in the computer program Artint (c) 2010.
cluster analysis intelligent building micro grid artificial neural network (ann) self-organizing map (som) kohonen map counter-propagation neural network type daily diagrams (tdd) load prediction