Name
Title | ||
|---|---|---|
A new fuzzy membership function for FSVM and its application in machinery fault diagnosis. |
Abstract | ||
|---|---|---|
In this paper, a new fuzzy membership function for fuzzy support vector machine is presented. It provides an effective approach to deal with the over-fitting problem when outliers exist in the training data set. Combining with the concept of the K-nearest neighbor algorithm, we give a definition of the new fuzzy membership function. Then, fuzzy support vector machine with some improvements is successfully applied in machinery fault diagnosis and some engineering experimental results show the good performance of the present approach. © 2012 IEEE. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICNC.2012.6234682 | ICNC |
Keywords | Field | DocType |
fuzzy membership function,fuzzy support vector machine,machinery fault diagnosis,testing,k nearest neighbor,fuzzy set theory,kernel,valves,machinery,support vector machines | Data mining,Neuro-fuzzy,Fuzzy classification,Defuzzification,Fuzzy set operations,Computer science,Support vector machine,Outlier,Fuzzy set,Artificial intelligence,Fuzzy number,Machine learning | Conference |
Volume | Issue | Citations |
null | null | 1 |
PageRank | References | Authors |
0.38 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao Tang | 1 | 15 | 7.02 |
| Yuhe Liao | 2 | 7 | 1.24 |
| Xiufeng Wang | 3 | 1 | 0.72 |