Traffic Prediction Using Ying-Yang Fuzzy Cerebellar Model Articulation Controller

Authors:
M. N. Nguyen;D. Shi;C. Quek;G. S. Ng
Affiliations:
Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Nanyang Technological University, Singapore
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Year:
2006

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Abstract

Traffic prediction is a critical element in traffic control today. With the increase of transportation, an effective traffic prediction allows to prevent traffic problems. This research aims to propose a novel approach to traffic prediction using Ying-Yang Fuzzy Cerebellar Model Articulation Controller (YYFCMAC). The model is motivated from the famous Chinese ancient Ying-Yang philosophy, which views everything as a product of conflict-harmony process between Ying and Yang. That principle is applied to find the optimal number of clusters and fuzzy sets in the fuzzification phase of the hybrid fuzzy-neural YYFCMAC network. The analyzed experiment on a set of real traffic data flow of the east-bound Pan Island Expressway (PIE) in Singapore shows the effectiveness of the YY-FCMAC in universal approximation and prediction.