Short-time Traffic Flow Prediction Method Based on Universal Organic Computing Architecture
- 10.2991/iccia.2012.303How to use a DOI?
- Short-time traffic flow, Organic computing, Particle Swarm Optimization algorithm, RBF Neural network
Designed a DNA-based genetic algorithm under the universal architecture of organic computing, combined particle swarm optimization algorithm, introduced a crossover operation for the particle location, can interfere with the particles’ speed, make inert particles escape the local optimum points, enhanced PSO algorithm's ability to get rid of local extreme point. Utilized improved algorithms to train the RBF neural network models, predict short-time traffic flow of a region intelligent traffic control. Simulation and error analysis of experimental results showed that, the designed algorithms can accurately forecast short-time traffic flow of the regional intelligent transportation control, forecasting effects is better, can be effectively applied to actual traffic engineering.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Shuzhi Nie AU - Yanhua Zhong AU - Ming Hu PY - 2014/05 DA - 2014/05 TI - Short-time Traffic Flow Prediction Method Based on Universal Organic Computing Architecture BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 1226 EP - 1229 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.303 DO - 10.2991/iccia.2012.303 ID - Nie2014/05 ER -