Sediment transport constantly influences river and civil structures and the lack ofinformation about its exact amount makes management efforts less effective. Hence,achieving a proper procedure to estimate the sediment load in rivers is important. We usedsupport vector machine model to estimate the sediments of the Kakareza River in LorestanProvince and the results were compared with those obta...

parameter estimation of the nonlinear muskingum model is a highly nonlinear optimization problem. although various techniques have been applied to optimize the coefficients of the nonlinear muskingum flood routing models, but an efficient method for this purpose in the calibration process is still lacking. the accuracy of artificial bee colony (abc) algorithm is investigated in this paper to op...

Shepperd and MacDonell “Evaluating prediction systems in software project estimation”. Information and Software Technology 54 (8), 820–827, 2012, proposed an improved measure of the effectiveness of predictors based on comparing them with random guessing. They suggest estimating the performance of random guessing using a Monte Carlo scheme which unfortunately excludes some correct guesses. This...

We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under the MAPE is equivalent to doing weighted Mean Absolute Error (MAE) regression. We show that universal consistency of Empirical Risk Minimization remains possible using the MAPE instead of the MAE.

A closed-form expression and an upper bound are obtained for the mean absolute error of the unbiased estimator of a probability in inverse binomial sampling. The results given permit the estimation of an arbitrary probability with a prescribed level of the normalized mean absolute error.