Identification of type daily diagrams of electric consumption based on cluster analysis of multi-dimensional data by neural network

Title:

Identification of type daily diagrams of electric consumption based on cluster analysis of multi-dimensional data by neural network

Creator:

Garlík, Bohumír and Křivan , Miloš

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:576913e0-c967-4c78-8ee5-1783e993d3ea
uuid:576913e0-c967-4c78-8ee5-1783e993d3ea
doi:10.14311/NNW.2013.23.017

Subject:

Artificial Neurqal Network (ANN), Self-Organizing Map (SOM), Kohonen map, counter-propagation neural network, cluster analysis, Type daily Diagram (TDD), load prediction, intelligent building, and micro grif

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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 © 2010.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2013 Volume:23 | Number:3

Harvested from:

CDK

Metadata only:

false