Name
Title | ||
|---|---|---|
Study On Comprehensive Evaluation Model Of Attribute Coordinate Based On Evaluation Sample Selection By K-Means |
Abstract | ||
|---|---|---|
It is a very important step that the sample points are marked by experts in the comprehensive evaluation method based on attribute coordinate. At present, the sample points are selected randomly in some algorithms. However, this method possibly causes that the sample points has the homogeneity and can not represent the whole sample space, thus affecting the precision of evaluation results. In this paper, K-means clustering method is used to select sample points for evaluation, and the corresponding simulation experiment is also carried out. Then the simulation results showed the advantages of improved algorithm. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3233/JCM-170732 | JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING |
Keywords | Field | DocType |
Attribute theory method, comprehensive evaluation, K-means | k-means clustering,Data mining,Pattern recognition,Computer science,Artificial intelligence,Sample selection | Journal |
Volume | Issue | ISSN |
17 | 3 | 1472-7978 |
Citations | PageRank | References |
1 | 0.39 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guanglin Xu | 1 | 26 | 9.95 |
| Xiaolin Xu | 2 | 268 | 25.21 |