In this paper, the data set generated by Bike Sharing System (BSS) has been modeled by a proposed method called fuzzy bivariate elliptic membership function that generates membership values between an independent variable and dependent variable whose functional form follows an ellipse since all numerical variables following a cyclic pattern such as season, month, hour, weather situation and so on. Besides, each membership value corresponding to each independent and dependent variable is used to find an aggregate outcome of a dependent variable based on a new decision-making tool. Therefore, how both weather and time combinations have an impact on the dependent variable could be derived. Since there is no built-in membership function available, the data set is used to construct a data-driven elliptic fuzzy membership function. Thus, the Chebyshev inequality based on the correlated variables is used to determine both the a and b parameters of the elliptic function representing 95% of the whole dataset.