S-Curve Regression of Fuzzy Method and Statistical Application

C.-W. Chen, C.-H. Tsai, K. Yeh, and C.-Y. Chen (Taiwan)


working capital management.


The least square method is in general used for curve fitting problem. We propose here a fuzzy S-curve regression model to deal with the case in which the observed data are given by fuzzy number. The fuzzy regression curve, obtained for project control of large-scale or small-scale engineering, is smoothly connected by a Takagi-Sugeno (T-S) fuzzy model. This paper also provide a concept that the upper bound and lower bound are given instead of confidence interval when the observed data are not obtained exactly. Based on the project cash flow and progress payment records of an example project taken from Department of Rapid Transit Systems, Taipei City Government, this model is demonstrated and tentative conclusions concerning the model are given. The developed S-curve equation could be used in a variety of applications related to project control in the working capital management of construction firms.

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