Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: concepts and techniques
Data mining: concepts and techniques
Evolving transfer functions for artificial neural networks
Neural Computing and Applications
Combined Use of Partial Least Squares Regression and Neural Network for Diagnosis Tasks
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Evaluation of adaptive neural network models for freeway incident detection
IEEE Transactions on Intelligent Transportation Systems
Development of Dual-Station Automated Expressway Incident Detection Algorithms
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Neural Networks
Hi-index | 12.05 |
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.