Conceptual cost estimation of pump stations projects using fuzzy clustering

Conceptual cost estimates, are prepared at the very early stages of a project, and generally before the construction drawings and specifications are available. At this stage, cost estimates are needed by the owner, contractor, designer, or funding agencies for determination of the feasibility of a project, financial evaluation of a number of alternative projects, or establishment of an initial budget. Traditional approaches rely heavily on experienced engineers. This paper presents a method using fuzzy clustering technique for pump station projects cost estimation. The proposed conceptual cost estimating methodology provides fast and reliable results that can be very useful in the early stages of a project. The main cost drivers are identified using stepwise regression. Collected data are utilized to build the fuzzy clustering model. A training data set and a testing data set are used to calibrate the model. Sensitivity analysis is conducted to determine the appropriate model and the corresponding number of clusters that provides minimum error.