Name
Abstract | ||
|---|---|---|
Fuzzy regression is one of important methods for data analysis. Fuzzy regression extends the concept of classical regression which has been constructed in the statistical framework. We show that a convex hull method can provide a powerful tool to reduce the computing time, especially for real-time data analysis. The main objective of this study is to propose an efficient real-time fuzzy regression analysis based on the use of convex hull, specifically a Beneath-Beyond algorithm. The reconstruction of convex hull edges depends on incoming vertices while a recomputing procedure can be implemented in real-time. An air pollution data is analyzed by applying the proposed approach. An important role of convex hull is emphasized in particular when dealing with the limitations of linear programming. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/FUZZY.2009.5277160 | Jeju Island |
Keywords | Field | DocType |
air pollution,convex programming,fuzzy set theory,regression analysis,air pollution,beneath-beyond algorithm,convex hull edge reconstruction,data analysis,linear programming,real-time fuzzy regression analysis,statistical framework | Data mining,Data modeling,Regression analysis,Computer science,Convex hull,Fuzzy set,Artificial intelligence,Linear programming,Fuzzy number,Output-sensitive algorithm,Mathematical optimization,Convex optimization,Machine learning | Conference |
ISSN | ISBN | Citations |
1098-7584 E-ISBN : 978-1-4244-3597-5 | 978-1-4244-3597-5 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Azizul Azhar Ramli | 1 | 16 | 5.25 |
| Junzo Watada | 2 | 411 | 84.53 |
| W. Pedrycz | 3 | 13966 | 1005.85 |