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Modelling GM(1,1) under the Criterion of the Minimization of Mean Absolute Percentage Error
Advanced Materials Research, 2012In this paper, we present two methods to estimate the parameters of the GM (1,1)model under. The criterion of the minimization of mean absolute percentage error (MAPE) (some authors called Average relative error).A linear programming method is used to optimize the whiting value of grey derivative of GM(1,1),four published articles are chosen for ...
Hai Jun Chen, Xi Juan Lou, Jie Liu
exaly +2 more sources
International Advances in Economic Research, 2009
Commonly used Mean Absolute Percentage Errors (MAPE) and the authors’ revised Mean Absolute Percentage Errors (RMAPE) are applied to measure the forecasting accuracy from different Moving Average Methods for independent time series. Simulation results show that both MAPE and RMAPE can only provide sensitive forecasting accuracy measurements on Moving ...
Louie Ren
exaly +2 more sources
Commonly used Mean Absolute Percentage Errors (MAPE) and the authors’ revised Mean Absolute Percentage Errors (RMAPE) are applied to measure the forecasting accuracy from different Moving Average Methods for independent time series. Simulation results show that both MAPE and RMAPE can only provide sensitive forecasting accuracy measurements on Moving ...
Louie Ren
exaly +2 more sources
Industry Xplore, 2023
The plastic resin coloring industry has a very important role in the molder supply chain. Materials must be imported from abroad with a long enough lead time, so material purchases are made based on the forecast provided by the molder. The constraints that occur are forecast inaccuracies which result in an increase in inventory level of material and a ...
Dwi Irwati, null Ade Nurul Hidayat
openaire +1 more source
The plastic resin coloring industry has a very important role in the molder supply chain. Materials must be imported from abroad with a long enough lead time, so material purchases are made based on the forecast provided by the molder. The constraints that occur are forecast inaccuracies which result in an increase in inventory level of material and a ...
Dwi Irwati, null Ade Nurul Hidayat
openaire +1 more source
INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, 2012
In order to establish a high-precision nonlinear forecasting model, the paper presents a new global optimization technique for parameters optimization in nonlinear forecasting model based on the minimization of mean absolute percentage error (MAPE). By implementation of an optimization technique based on the successive use of a genetic algorithm and of
Haijun Chen - +3 more
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In order to establish a high-precision nonlinear forecasting model, the paper presents a new global optimization technique for parameters optimization in nonlinear forecasting model based on the minimization of mean absolute percentage error (MAPE). By implementation of an optimization technique based on the successive use of a genetic algorithm and of
Haijun Chen - +3 more
openaire +1 more source
Measuring Relative Accuracy: A Better Alternative to Mean Absolute Percentage Error
SSRN Electronic Journal, 2013Surveys show that the mean absolute percentage error (MAPE) is the most widely used measure of forecast accuracy in businesses and organizations. It is also used to compare accuracy across multiple data sets, e.g. when choosing a forecasting method. Yet this metric systematically favours methods which under-forecast.
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Root mean square error or mean absolute error? Use their ratio as well
Information Sciences, 2022exaly
On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression
IEEE Signal Processing Letters, 2020Jun Qi +2 more
exaly