Name
Abstract | ||
|---|---|---|
Fuzzy clustering procedures based on the FCM algorithm calculate group membership probabilities or degrees taking into account the distance between objects and group prototypes. This paper seeks to improve the computation of such membership probabilities by a new membership function which also reflects the relative position of an object with respect to each group. By this way, some illogical results are avoided and a convex partition is provided. Finally, numerical examples illustrate the performance of the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.fss.2007.08.016 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
fuzzy clustering procedure,convex partition,new membership function,relative position,group membership probability,fuzzy clustering partition,membership probability,improving probability,numerical example,illogical result,group prototype,proposed algorithm,fuzzy clustering,membership function | Fuzzy clustering,Fuzzy classification,Algorithm,Fuzzy set,Probability distribution,Artificial intelligence,Fuzzy control system,Partition (number theory),Membership function,Machine learning,Mathematics,Computation | Journal |
Volume | Issue | ISSN |
159 | 4 | Fuzzy Sets and Systems |
Citations | PageRank | References |
4 | 0.45 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jesús A. Soto | 1 | 13 | 2.67 |
| Antonio Flores-Sintas | 2 | 38 | 4.93 |
| Javier Palarea-Albaladejo | 3 | 12 | 2.53 |