Name
Abstract | ||
|---|---|---|
When vehicles and pedestrians increase greatly, road traffic accidents occur frequently, which attracts our attention. In order to solve that problem, it is necessary for us to make reasonable evaluation on the road safety level. This paper will adopt fuzzy clustering analysis, fuzzy mathematics and relative knowledge to make clustering analysis on the road safety level. We can set up some road safety policies and measures based on the result of fuzzy clustering on the road safety level. For example, government departments can increase the number of traffic police or traffic lights and so on. For a new road, we can classify it into the existing classes according to the collected data to improve the management and reduce the number of accidents. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/FSKD.2013.6816221 | 2013 10TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD) |
Keywords | Field | DocType |
fuzzy clustering, the road safety, fuzzy similar matrix, fuzzy equivalence matrix | Fuzzy clustering,Computer science,Fuzzy mathematics,Road traffic,Vehicle Information and Communication System,Traffic police,Artificial intelligence,Cluster analysis,Standardization,Machine learning,Government | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Renyuan Wang | 1 | 0 | 0.34 |
| Yan Chen | 2 | 163 | 23.47 |
| Taoying Li | 3 | 18 | 4.68 |
| Penghui Li | 4 | 1 | 0.72 |
| Junxiong Sun | 5 | 0 | 0.34 |