Hierarchical fuzzy rule-based system optimized with genetic algorithms for short term traffic congestion prediction
Data about 87 loop detectors in a real highway during a month is taken. 3 Datasets about congestion in the next 5, 15 and 30min are defined. A codification for hierarchical fuzzy rule-based system is stated. A genetic algorithm to optimize such hierarchical systems is implemented. Results are compared with other classifiers in terms of accuracy and simplicity.
hierarchical fuzzy rule-based systems genetic algorithms traffic congestion prediction intelligent transportation systems congestion forecasting genetic fuzzy systems