A platform for research: civil engineering, architecture and urbanism
Enhancing Neural Network Traffic Incident‐Detection Algorithms Using Wavelets
Researchers have presented freeway traffic incident‐detection algorithms by combining the adaptive learning capability of neural networks with imprecision modeling capability of fuzzy logic. In this article it is shown that the performance of a fuzzy neural network algorithm can be improved through preprocessing of data using a wavelet‐based feature‐extraction model. In particular, the discrete wavelet transform (DWT) denoising and feature‐extraction model proposed by Samant and Adeli (2000) is combined with the fuzzy neural network approach presented by Hsiao et al. (1994). It is shown that substantial improvement can be achieved using the data filtered by DWT. Use of the wavelet theory to denoise the traffic data increases the incident‐detection rate, reduces the false‐alarm rate and the incident‐detection time, and improves the convergence of the neural network training algorithm substantially.
Enhancing Neural Network Traffic Incident‐Detection Algorithms Using Wavelets
Researchers have presented freeway traffic incident‐detection algorithms by combining the adaptive learning capability of neural networks with imprecision modeling capability of fuzzy logic. In this article it is shown that the performance of a fuzzy neural network algorithm can be improved through preprocessing of data using a wavelet‐based feature‐extraction model. In particular, the discrete wavelet transform (DWT) denoising and feature‐extraction model proposed by Samant and Adeli (2000) is combined with the fuzzy neural network approach presented by Hsiao et al. (1994). It is shown that substantial improvement can be achieved using the data filtered by DWT. Use of the wavelet theory to denoise the traffic data increases the incident‐detection rate, reduces the false‐alarm rate and the incident‐detection time, and improves the convergence of the neural network training algorithm substantially.
Enhancing Neural Network Traffic Incident‐Detection Algorithms Using Wavelets
Samant, A. (author) / Adeli, H. (author)
Computer‐Aided Civil and Infrastructure Engineering ; 16 ; 239-245
2001-07-01
7 pages
Article (Journal)
Electronic Resource
English
Enhancing Neural Network Traffic Incident-Detection Algorithms Using Wavelets
Online Contents | 2001
|Incorporating Neural Network Traffic Prediction into Freeway Incident Detection
British Library Online Contents | 1999
|Developed Incident Detection Algorithm Compared with Neural Network Algorithms
British Library Online Contents | 2003
|An Adaptive Conjugate Gradient Neural Network-Wavelet Model for Traffic Incident Detection
Online Contents | 2000
|