Application of an efficient nonlinear regression technique for sewer cost modelling

Abstract

This article investigates the effectiveness of a nonlinear regression technique for estimating the empirical parameters contained in a separable and a generalized cost functions. The regression technique needs only to optimize the values of the nonlinear parameters and thus makes it considerably easier for a user to employ it for modelling of a sewer cost function. The results of this study indicated that the regression technique is capable of providing a set of reasonably good estimates for the empirical parameters contained in the cost models under a wide range of initial guessed solutions and under a wide level of incorporate noise. In addition, the two types of cost models investigated were found to be rather insensitive to some minor errors in the estimated values of its model parameters.