Benchmarking is one of several regulatory tools to encourage continuous improvement of water utility operations and to evaluate utility performance. Regulators of water utilities can use benchmarking, in conjunction with incentive regulation, to reward efficient utilities that provide high quality service. However, benchmarking requires careful planning. This article, the fourth in a series abo...

We report a benchmarking of neural networks and regression techniques in a time series forecasting task. The estimation errors, computing costs and additional information obtained by Bayesian neural networks are compared with other neural network models and with Multivariate Adaptive Regression Splines (MARS). The Mackey Glass time series in chaotic regime was used to generate the two data sets...

This work presents a new technique for temporally benchmarking a time series according to the growth rates preservation principle (GRP) by Causey and Trager (1981). A procedure is developed which (i) transforms the original constrained problem into an unconstrained one, and (ii) applies a Newton’s method exploiting the analytic Hessian of the GRP objective function. We show that the proposed te...

in this paper, we propose a new residual analysis method using fourier series transform into fuzzy time series model for improving the forecasting performance. this hybrid model takes advantage of the high predictable power of fuzzy time series model and fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

Dynamic time warping constitutes a major tool for analyzing time series. In particular, computing a mean series of a given sample of series in dynamic time warping spaces (by minimizing the Fréchet function) is a challenging computational problem, so far solved by several heuristic, inexact strategies. We spot several inaccuracies in the literature on exact mean computation in dynamic time warp...