MPAR-CLUSTER: APPLIED ALGORITHM OF GEO-SELECTION FOR OTIMIZATION OF THE CREDIT RECOVERY OF ELECTRICITY SUPPLY
ISBN 978-85-88783-11-9
Authors
1Rodrigues, M.P.; 2Copque, A.
1COELBA Email: mprates@coelba.com.br
2UCSAL/COELBA Email: augustocopque@gmail.com
Abstract
This paper presents a study of optimization of operational recovery credit default with geoprocessing use through Geoprocessing tools , developed in the Receivables Management Companhia de Eletricidade do Estado da Bahia - COELBA sector . The work was initially based on the application of Data Mining Tools for Software KNIME 2.9 and later use of the tool of GIS - ArcGIS 10.1/ESRI . Were evaluated and applied analytical processing algorithms , to improve the process of spatial selection and define the best sets logistical credit recovery . The focus study , based on geoprocessing use in cutting action is due to the fact that this process has the largest collection efficiency . It is understood that the efficiency of the cutting action , should the great importance that electricity has on modern life . The research was guided its evolution from analysis of algorithms agglutination and georeferenced database , whose focus was and is acting in the cutting action due to the fact that this process has the largest collection efficiency . For the implementation of the study , through some geoprocessing techniques, the Mpar - cluster , this optimization model was developed from a custom algorithm for spatial selection, that had with subsidy: information stored in geographic databases , database information alphanumeric, images (aerial photographs and satellite images), text files , and digital tables.