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A NEW VIEWPOINT OF S-CURVE REGRESSION MODEL AND ITS APPLICATION TO CONSTRUCTION MANAGEMENT
76
Citations
13
References
2006
Year
EngineeringFuzzy ModelingPerformance-based Building DesignIndustrial EngineeringDeterioration ModelingOperations ResearchBuilt EnvironmentSystems EngineeringFuzzy OptimizationAutomation In ConstructionStatisticsQuantitative ManagementFuzzy LogicUpper BoundConstruction TechnologyBuilding PerformanceFuzzy Regression CurveCivil EngineeringFuzzy Expert SystemRobust Fuzzy ProgrammingConstruction ManagementCurve Fitting ProblemsConstruction Engineering
The least square method is in generally used for curve fitting problems. We here propose a fuzzy S-curve regression model to deal with the case in which the observed data are given by fuzzy numbers. The fuzzy regression curve, obtained for project control and predicting the progress of large-scale or small-scale engineering, is smoothly connected by a Takagi-Sugeno (T-S) fuzzy model. This paper also proposes the concept that the upper bound and lower bound are given instead of the 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 the Department of Rapid Transit Systems, Taipei City Government, this model is demonstrated and tentative conclusions concerning the model are given. The S-curve equation developed here could be used in a variety of applications related to project control for the management of working capital for construction firms.
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