Best Practices for Road Weather Management Version 2.0
Title:
An Application of Neural Network on Traffic Speed Prediction under Adverse Weather Condition
Abstract:
A neural network model for predicting traffic speed under adverse weather conditions is proposed. One link located in Chicago was chosen and all the data involved was collected from the Internet. The Back Propagation algorithm was used to train the neural network model for approaching the best prediction results. The MATLAB software was used to solve this model. The result has demonstrated that, neural network is an effective tool theory to predict traffic situation if appropriate model architecture and input data are available.
Source(s):
82nd Transportation Research Board (TRB) Annual Meeting. For an electronic copy of this resource, please direct your request to WeatherFeedback@dot.gov.
Date: 2003
Author:
Huang, Ran
Keywords:
Speed
Traffic modeling
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