Abstract
The value of K is always confirmed in advance to exert K-means algorithm of spatial clustering. However, it can not be clearly and easily confirmed in fact for its uncertainty. A distance cost function was recommended. A corresponding math model was set up and a new optimization algorithm of K value was designed. A preliminary study on the optimization of K value for spatial clustering was realized by a simulation design.
| Original language | English |
|---|---|
| Pages (from-to) | 573-576 |
| Number of pages | 4 |
| Journal | Xitong Fangzhen Xuebao / Journal of System Simulation |
| Volume | 18 |
| Issue number | 3 |
| State | Published - Mar 2006 |
| Externally published | Yes |
Keywords
- Distance cost function
- K-means algorithm
- Optimization of K
- Spatial clustering