Analysis of Forecasting Methods of Time-Series with Increasing Trends

被引：0
作者：
De la Torre Bucio, Jesus [1 ]
Ramos Paz, Antonio [1 ]
Aurelio Medina Rios, J. [1 ]
机构：
[1] Univ Michoacana, Fac Ingn Elect, Morelia, Michoacan, Mexico
来源：
PROCEEDINGS OF THE 2021 XXIII IEEE INTERNATIONAL AUTUMN MEETING ON POWER, ELECTRONICS AND COMPUTING (ROPEC 2021) | 2021年
关键词：
Exponential Smoothing; Forecast; Holt-Winters; Least Squares; MatLab; Moving Averages; Naive; Time series; Weighted Moving Averages;
D O I：
10.1109/ROPEC53248.2021.9668024
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
This paper presents the applications of different time series forecasting methods to predict an annual period of passengers compares the efficiency between the different models through the mean absolute percentage error (MAPE) and uses MatLab (R) as a computational tool to carry out each forecasting model.
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页数：6
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