Name
Title | ||
|---|---|---|
Short term traffic forecasting based on hybrid of firefly algorithm and least squares support vector machine |
Abstract | ||
|---|---|---|
The goal of an active traffic management is to manage congestion based on current and predicted traffic conditions. This can be achieved by utilizing traffic historical data to forecast the traffic flow which later supports travellers for a better journey planning. In this study, a new method that integrates Firefly algorithm (FA) with Least Squares Support Vector Machine (LSSVM) is proposed for short term traffic speed forecasting, which is later termed as FA-LSSVM. In particular, the Firefly algorithm which has the advantage in global search is used to optimize the hyper-parameters of LSSVM for efficient data training. Experimental result indicates that the proposed FA-LSSVM generates lower error rate and a higher accuracy compared to a non-optimized LSSVM. Such a scenario indicates that FA-LSSVM would be a competitor method in the area of time series forecasting. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-981-287-936-3_16 | Communications in Computer and Information Science |
Keywords | Field | DocType |
short term forecasting,Least Squares Support Vector Machine,Firefly algorithm,traffic management system | Time series,Mathematical optimization,Traffic flow,Least squares support vector machine,Computer science,Word error rate,Firefly algorithm,Traffic conditions,Active traffic management | Conference |
Volume | ISSN | Citations |
545 | 1865-0929 | 1 |
PageRank | References | Authors |
0.36 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuhanis Yusof | 1 | 27 | 8.35 |
| Farzana Kabir Ahmad | 2 | 4 | 3.20 |
| Siti Sakira Kamaruddin | 3 | 16 | 3.41 |
| Hasbullah Omar | 4 | 1 | 2.73 |
| athraa jasim mohamed | 5 | 1 | 0.36 |