Results 11 to 20 of about 6,507,288 (274)

Using the Mean Absolute Percentage Error for Regression Models

open access: yesCoRR, 2015
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.
de Myttenaere, Arnaud   +3 more
openaire   +6 more sources

Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector

open access: yesWorld Congress on Mechanical, Chemical, and Material Engineering
The research work is based on the analysis of demand in a tourism company using mathematical models. The methodology design presents a correlational and descriptive scope where the company's sales are collected to calculate the mean absolute percentage error in demand.
Ludeña Roman, Sayuri Arleth Renatta   +2 more
openaire   +3 more sources

Prediction of Infectious Disease to Reduce the Computation Stress on Medical and Health Care Facilitators

open access: yesMathematics, 2023
Prediction of the infectious disease is a potential research area from the decades. With the progress in medical science, early anticipation of the disease spread becomes more meaningful when the resources are limited. Also spread prediction with limited
Shalini Shekhawat   +3 more
doaj   +1 more source

Metode Double Exponential Smoothing pada Sistem Peramalan Tingkat Kemiskinan Kabupaten Pangkep

open access: yesIlkom Jurnal Ilmiah, 2020
Peramalan adalah kegiatan memperkirakan kejadian yang akan terjadi berdasarkan historical data kuantitatif suatu kejadian. Peramalan sering digunakan oleh pemerintah dalam membuat suatu kebijakan.
Nur Almar' Atussaliha   +2 more
doaj   +1 more source

Mean absolute error (MAE), R squared, root mean squared error (RMSE), symmetric mean absolute percentage error (SMAPE) for train, test & validation data.

open access: yes, 2023
Mean absolute error (MAE), R squared, root mean squared error (RMSE), symmetric mean absolute percentage error (SMAPE) for train, test & validation data.
Swapnashree Satapathy (15426889)   +9 more
core   +1 more source

Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not [PDF]

open access: yes, 2022
The root-mean-squared error (RMSE) and mean absolute error (MAE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it to the reader to decide ...
T. O. Hodson   +2 more
core   +2 more sources

Penerapan Metode Double Exponential Smoothing dan Moving Average pada Peramalan Permintaan Produk Gasket Cap di PT. Nesinak Industries

open access: yesJurnal Serambi Engineering, 2022
PT. Nesinak Industries is a company which focuses on the manufacturing process of an electronic component as well as automotive components (vehicle). In business activities, such as production, a strategy is required to survive in competition.
Muhammad Hafidh Kurniawan, Dene Herwanto
doaj   +1 more source

Mean-risk models using two risk measures: A multi-objective approach [PDF]

open access: yes, 2006
This paper proposes a model for portfolio optimisation, in which distributions are characterised and compared on the basis of three statistics: the expected value, the variance and the CVaR at a specified confidence level.
Diana Roman   +5 more
core   +7 more sources

Forecasting of Groundwater Tax Revenue Using Single Exponential Smoothing Method [PDF]

open access: yesE3S Web of Conferences, 2019
Setting the target of groundwater tax revenues for the next year is an important thing for Kutai Kartanegara Regional Office of Revenue to maximize the regional income and accelerate regional development.
Khairina Dyna Marisa   +3 more
doaj   +1 more source

A multi-variable multi-step Seq2seq networks for the state of charge estimation of lithium-ion battery

open access: yesCase Studies in Thermal Engineering, 2023
Due to the complexity and changeable of lithium-ion batteries, we propose a multi-variable and multi-step Temporal neural network to cover this task. Specially, a novel multi-step training strategy is applied to deal with long time sequences, and multi ...
Yufeng Huang, Jian Sun, Lei Xu
doaj   +1 more source

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