Name
Title | ||
|---|---|---|
A hybrid model of partial least squares and neural network for traffic incident detection |
Abstract | ||
|---|---|---|
Development of a universal freeway incident detection algorithm is a task that remains unfulfilled and many promising approaches have been recently explored. The partial least squares (PLS) method and artificial neural network (NN) were found in previous studies to yield superior incident detection performance. In this article, a hybrid model which combines PLS and NN is developed to detect automatically traffic incident. A real traffic data set collected from motorways A12 in the Netherlands is presented to illustrate such an approach. Data cleansing has been introduced to preprocess traffic data sets to improve the data quality in order to increase the veracity and reliability of incident model. The detection performance is evaluated by the common criteria including detection rate, false alarm rate, mean time to detection, classification rate and the area under the curve (AUC) of the receiver operating characteristic. Computational results indicate that the hybrid approach is capable of increasing detection performance comparing to PLS, and simplifying the NN structure for incident detection. The hybrid model is a promising alternative to the usual PLS or NN for incident detection. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.eswa.2011.09.158 | Expert Syst. Appl. |
Keywords | Field | DocType |
neural network,superior incident detection performance,hybrid model,incident model,detection rate,universal freeway incident detection,data cleansing,nn structure,incident detection,traffic incident,traffic incident detection,detection performance,partial least squares | Data mining,Data cleansing,Data set,Data quality,Receiver operating characteristic,Computer science,Partial least squares regression,Common Criteria,Artificial intelligence,Constant false alarm rate,Artificial neural network,Machine learning | Journal |
Volume | Issue | ISSN |
39 | 5 | 0957-4174 |
Citations | PageRank | References |
7 | 0.57 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jian Lu | 1 | 33 | 2.76 |
| Shuyan Chen | 2 | 54 | 4.40 |
| Wei Wang | 3 | 93 | 11.54 |
| Henk van Zuylen | 4 | 69 | 5.89 |