Name
Abstract | ||
|---|---|---|
Regression models are well known and widely used as one of the important models in system modeling. In this paper, we extend the concept of regression models in order to handle hybrid data coming from various sources of data quite often exhibiting diverse levels of quality. The major objective of this study is to develop a convex hull method being regarded as a potential vehicle, which helps reduce the computing time, especially in real-time data analysis as well as an overall computational complexity. We propose an efficient real-time fuzzy switching regression analysis based on the convex hull approach in which a Beneath-Beyond algorithm is employed to design a convex hull. The method addresses situations when we have to deal with heterogeneous data. In the proposed design setting, we emphasize a pivotal role of convex hull approach which is crucial when alleviating limitations of a linear programming manifesting in system modeling. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1806338.1806391 | iiWAS |
Keywords | Field | DocType |
convex hull,system modeling,real-time data analysis,heterogeneous data,hybrid data,regression model,convex hull approach,regression analysis,method addresses situation,convex hull method,real time,linear program,computational complexity,real time data | Data mining,Mathematical optimization,Regression analysis,Computer science,Fuzzy logic,Convex hull,Systems modeling,Linear programming,Proper convex function,Output-sensitive algorithm,Computational complexity theory | Conference |
Citations | PageRank | References |
3 | 0.42 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Azizul Azhar Ramli | 1 | 16 | 5.25 |
| Junzo Watada | 2 | 411 | 84.53 |
| W. Pedrycz | 3 | 13966 | 1005.85 |