Search

In order to solve the problems of missing traffic flow data caused by various reasons such as weather effect, detector faults and artificial error etc., this paper proposed a method based on the fuzzy rough set theory to impute missing traffic flow data. We combined the support vector clustering and fuzzy rough set to classify traffic flow data, and then combined the fuzzy neural network and genetic algorithm to impute missing data. The method optimized the support vector clustering parameters, cluster size and weighting factor, and estimated the missing values. The results of the study showed that the proposed novel hybrid method produced sufficient and reasonable data imputation performance results. Compared with the results of fuzzy neural network and other estimation models, the data imputation effect of this model was better than other comparison models. [ABSTRACT FROM AUTHOR]