Name
Abstract | ||
|---|---|---|
•Define key congestion points and convert it to a feature selection problem.•Propose an expert system to discover key congestion points of urban traffic.•Revise BSSReduce, which runs 15 times faster than BSSReduce for this data.•Discover 75 and 300 key congestion points from over 10,000 and 50,000 points. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2020.113544 | Expert Systems with Applications |
Keywords | DocType | Volume |
Key points of congestion,BSSReduce,Digital map,Feature selection,Soft sets,Rough sets | Journal | 158 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ke Gong | 1 | 74 | 5.10 |
| Li Zhang | 2 | 15 | 3.31 |
| Du Ni | 3 | 0 | 1.01 |
| Huamin Li | 4 | 0 | 0.68 |
| Maozeng Xu | 5 | 36 | 5.92 |
| Yong Wang | 6 | 10 | 5.06 |
| Yuanxiang Dong | 7 | 0 | 0.34 |