| Title | An Overview of Parameter and Data Strategies for k-Nearest Neighbours Based Short-Term Traffic Prediction |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Sun, Bin, Cheng, Wei, Goswami, Prashant, Bai, Guohua |
| Conference Name | Proceedings of the 2017 International Conference on E-Society, E-Education and E-Technology |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-5376-2 |
| Keywords | k-Nearest Neighbours Regression, Measurement, Metrics, nearest neighbor search, Parameter and Data Strategies, pubcrawl, Short-Term Traffic Prediction |
| Abstract | Modern intelligent transportation systems (ITS) requires reliable and accurate short-term traffic prediction. One widely used method to predict traffic is k-nearest neighbours (kNN). Though many studies have tried to improve kNN with parameter strategies and data strategies, there is no comprehensive analysis of those strategies. This paper aims to analyse kNN strategies and guide future work to select the right strategy to improve prediction accuracy. Firstly, we examine the relations among three kNN parameters, which are: number of nearest neighbours (k), search step length (d) and window size (v). We also analysed predict step ahead (m) which is not a parameter but a user requirement and configuration. The analyses indicate that the relations among parameters are compound especially when traffic flow states are considered. The results show that strategy of using v leads to outstanding accuracy improvement. Later, we compare different data strategies such as flow-aware and time-aware ones together with ensemble strategies. The experiments show that the flow-aware strategy performs better than the time-aware one. Thus, we suggest considering all parameter strategies simultaneously as ensemble strategies especially by including v in flow-aware strategies. |
| URL | http://doi.acm.org/10.1145/3157737.3157749 |
| DOI | 10.1145/3157737.3157749 |
| Citation Key | sun_overview_2017 |
An Overview of Parameter and Data Strategies for k-Nearest Neighbours Based Short-Term Traffic Prediction