In this paper, we present the modeling of time series data which are corrupted by noise via nonsingleton fuzzy logic system. Nonsingleton fuzzy logic system (NFLS) is useful in cases where the available data are corrupted by noise. NFLS is a fuzzy system whose inputs are modeled as fuzzy number. The abilities of NFLS to approximate arbitrary functions, and to effectively deal with noise and uncertainty, are used to analyze corrupted time series data. In the simulation results, we compare the results of the NFLS approach with the results of using only a traditional fuzzy logic system.