A fuzzy modeling method using rough sets and its applications to intelligent transportation systems

Combining rough sets and fuzzy sets together, a fuzzy modeling method is put forward. Using information reasoning and data mining technology, a rough fuzzy model of four-phase intersections is built from the measured data and the model has been successfully used in the simulation research of traffic control systems. The examples show that this method is simple and available. It can make the best of reducing the model error when directly extracting the fuzzy rules from the insufficient experience. Using the method given in this paper, the optimal and objective models for any traffic control systems can be extracted from historical data.