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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
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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
2025 3rd International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE)
Ananda Hadi Elyas +3 more
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Ananda Hadi Elyas +3 more
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Dynamic mean absolute error as new measure for assessing forecasting errors
Energy Conversion and Management, 2018Laura Frías-Paredes +2 more
exaly
Journal of Machine Intelligence and Data Science
Sayuri Arleth Renatta Ludeña Román +2 more
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Sayuri Arleth Renatta Ludeña Román +2 more
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Assessing the statistical characteristics of the mean absolute error or forecasting
International Journal of Forecasting, 1991Wen Lea Pearn
exaly

