Name
Abstract | ||
|---|---|---|
Rough set is an emergent technique of soft computing that have been used in many knowledge discovery in database applications. This work describes an application of rough sets in the fraud detection of electrical energy consumers. From an information system, rough sets concept of reduct was used to reduce the number of conditional attributes and the minimal decision algorithm (MDA) was used to reduce some values of conditional attributes. The reduced information system derives a set of rules that reaches consumers behavior, allowing the classification rule system to predict many fraud consumers profiles. Rough sets prove that it is a powerful technique with application in many systems based in data. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICSMC.2004.1400905 | Systems, Man and Cybernetics, 2004 IEEE International Conference |
Keywords | Field | DocType |
data mining,electricity supply industry,fraud,power consumption,rough set theory,classification rule system,electrical energy consumers,fraud detection,minimal decision algorithm,reduced information system,rough set theory,soft computing | Information system,Data mining,Reduct,Classification rule,Computer science,Electric potential energy,Rough set,Knowledge extraction,Artificial intelligence,Soft computing,Machine learning,Power consumption | Conference |
Volume | ISSN | ISBN |
4 | 1062-922X | 0-7803-8566-7 |
Citations | PageRank | References |
16 | 1.36 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Edison Cabral | 1 | 19 | 1.88 |
| Edgar M. Gontijo | 2 | 19 | 1.88 |