Name
Abstract | ||
|---|---|---|
Recently, the analysis of power load in the electrical industry has becomes an important element for the concern of customer safety. In power system related studies, data mining techniques are used in power load analysis and they can help decision making in the electrical industry. In this paper, for using emerging patterns to define and analyze the significant difference of safe and non-safe power load lines, and identifying which line is potentially unsafe, we proposed an incremental TFP-tree algorithm for mining emerging patterns that can search efficiently within memory limitation. Especially, the use of two different minimum supports makes the algorithm possible to mine most number of emerging patterns and efficiently handle the incrementally increased, large size of data sets such as power consumption data. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-24082-9_86 | ICHIT (1) |
Keywords | Field | DocType |
electrical industry,power load,power load analysis,customer safety,power consumption data,patterns mining,data mining technique,enumeration tree,non-safe power load line,different support,power system,different minimum support,incremental tfp-tree algorithm | Data mining,Data set,Computer science,Enumeration,Electric power system,Electric power industry,Power consumption,Distributed computing | Conference |
Citations | PageRank | References |
1 | 0.36 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minghao Piao | 1 | 37 | 6.30 |
| Jong Bum Lee | 2 | 1 | 1.03 |
| Ho Sun Shon | 3 | 38 | 8.00 |
| Unil Yun | 4 | 969 | 55.33 |
| Keun Ho Ryu | 5 | 883 | 85.61 |