A Set of Time Series Forecasting Models Based on the Ordered Difference

被引：0

作者：

Wang, Hongxu ^{[1
]}

Yin, Chengguo ^{[2
]}

Lu, Xiaoli ^{[1
]}

Feng, Hao ^{[3
]}

Fu, Xiaofang ^{[2
]}

机构：

[1] Hainan Trop Ocean Univ, Sch Ocean Business, Sanya, Hainan, Peoples R China

[2] Hainan Trop Ocean Univ, Sch Ocean Informat Engn, Sanya, Hainan, Peoples R China

[3] Hainan Trop Ocean Univ, Sch Ocean Sci & Technol, Sanya, Hainan, Peoples R China

来源：

PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELING AND SIMULATION (AMMS 2017) | 2017年 / 153卷

关键词：

time series; automatic optimization search method; the fractional sum function of ASOD; the inverse function of fractional sum function of ASOD; the forecasting function of ASOD;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A set of time series forecasting models based on the ordered difference of historical data (ASOD) is proposed. For a time series, the automatic optimization search method can be applied to sieve standard time series forecasting model Cp(k, h) in ASOD, so that in simulating the prediction of historical data of the time series, the predicted values can reach AFER (Average Forecasting Error Rate) = 0% and MSE (Mean Square Error) = 0. For instance, for the enrollment of the University of Alabama in 1971- 1992, the automatic optimization search method can be applied to sieve standard time series forecasting model Cp(0.0003,0.0003), the problem that the prediction accuracy of fuzzy time series forecasting model is not ideal for many years has been solved.

引用

页码：128 / 131

页数：4

共 50 条

[21] Forecasting models for prediction in time series
Carpinteiro, Otavio A. S.
Leite, Joao P. R. R.
Pinheiro, Carlos A. M.
Lima, Isaias
[J]. ARTIFICIAL INTELLIGENCE REVIEW, 2012, 38 (02) : 163 - 171
[22] Hesitant fuzzy set based computational method for financial time series forecasting
Kamlesh Bisht
Sanjay Kumar
[J]. Granular Computing, 2019, 4 : 655 - 669
[23] Study and application of time series forecasting based on rough set and Kernel method
Shu-xia Yang
[J]. Journal of Central South University of Technology, 2008, 15 : 336 - 340
[24] Study and application of time series forecasting based on rough set and Kernel method
杨淑霞
[J]. Journal of Central South University of Technology, 2008, 15(S2) (S2) : 336 - 340
[25] Study and application of time series forecasting based on rough set and Kernel method
Yang Shu-xia
[J]. JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY, 2008, 15 (Suppl 2): : 336 - 340
[26] Hesitant fuzzy set based computational method for financial time series forecasting
Bisht, Kamlesh
Kumar, Sanjay
[J]. GRANULAR COMPUTING, 2019, 4 (04) : 655 - 669
[27] Bernoulli Difference Time Series Models
Alzaid, Abulhamid A.
Omair, Maha A.
Alhadlaq, Weaam M.
[J]. CHILEAN JOURNAL OF STATISTICS, 2016, 7 (01): : 55 - 65
[28] Study and application of time series forecasting based on rough set and Kernel method
杨淑霞
[J]. Journal of Central South University, 2008, 15 (S2) : 336 - 340
[29] Forecasting of Fuzzy Time Series Based on the Concept of the Nearest Fuzzy Sets and Tensor Models of Time Series
Yu. M. Minaev
O. Yu. Filimonova
Yu. I. Minaeva
[J]. Cybernetics and Systems Analysis, 2023, 59 : 165 - 176
[30] Forecasting of Fuzzy Time Series Based on the Concept of the Nearest Fuzzy Sets and Tensor Models of Time Series
Minaev, Yu. M.
Filimonova, O. Yu.
Minaeva, Yu. I.
[J]. CYBERNETICS AND SYSTEMS ANALYSIS, 2023, 59 (01) : 165 - 176

← 1 2 3 4 5 →