Name
Abstract | ||
|---|---|---|
The objective of this work is to develop a system that pre-select electricity energy company customers who will undergo in-site inspection for frauds or faulty measurement equipments identification. The pre-selection system was built based on the electricity company database. It used attributes such as monthly energy consumption, type of consumers, previous inspection outcome, and others. A decision tree based classification system was used to reach such goal. The identification was designed, trained and tested using MATLAB code. The fraud/faulty equipments identification per number of in-site inspection rate was 40% of the total of pre-selected customers, which was above the expectation. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICSMC.2004.1400924 | Systems, Man and Cybernetics, 2004 IEEE International Conference |
Keywords | Field | DocType |
data mining,decision trees,electricity supply industry,fraud,MATLAB code,classification system,consumer type,decision tree,electricity company customers,faulty measurement equipments identification,fraud identification,in-site inspection,monthly energy consumption,previous inspection outcome | Decision tree,Data mining,MATLAB,Computer science,Electricity,Operations research,Artificial intelligence,Energy consumption,Machine learning | Conference |
Volume | ISSN | ISBN |
4 | 1062-922X | 0-7803-8566-7 |
Citations | PageRank | References |
3 | 0.53 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. R. Filho | 1 | 3 | 0.53 |
| Edgar M. Gontijo | 2 | 19 | 1.88 |
| Antonio C. Delaiba | 3 | 3 | 0.53 |
| Evandro Mazina | 4 | 3 | 0.53 |
| José Edison Cabral | 5 | 19 | 1.88 |
| João O. P. Pinto | 6 | 30 | 8.37 |