Choosing the appropriate order in fuzzy time series: A new N-factor fuzzy time series for prediction of the auto industry production

被引：25

作者：

Avazbeigi, Milad ^{[1
]}

Doulabi, Seyed Hossein Hashemi ^{[1
]}

Karimi, Behrooz ^{[1
]}

机构：

[1] Amirkabir Univ Technol, Dept Ind Engn, Tehran, Iran

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 08期

关键词：

N-factor high-order fuzzy time series; N-factor high-order fuzzy logical relationships; Tabu Search (TS); Parametric fuzzy inference system; Degree of firing; Auto industry production; FORECASTING ENROLLMENTS; TEMPERATURE PREDICTION; LOGICAL RELATIONSHIPS; INTERVALS; LENGTHS;

D O I：

10.1016/j.eswa.2010.02.049

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new fuzzy time series based on high-order fuzzy logical relationships and Tabu Search is presented. The proposed method constructs N-factor high-order fuzzy logical relationships based on the historical data and uses Tabu Search and a parametric fuzzy inference system to adjust the length of intervals in the universe of discourse for prediction to increase the forecasting accuracy rate. We have applied our model for different cases with different factors. The model is applied for prediction of auto industry production of Iranian companies with a three-factor fuzzy time series model. The results show that the proposed method gets a higher forecasting accuracy rate than the existing methods in all cases. (c) 2010 Elsevier Ltd. All rights reserved.

引用

页码：5630 / 5639

页数：10

共 29 条

[1]

[Anonymous], 1986, C NUM METH COMB OPT

[2] Forecasting enrollments based on fuzzy time series [J].

Chen, SM .

FUZZY SETS AND SYSTEMS, 1996, 81 (03) :311-319

[3] Entropy-based and trapezoid fuzzification-based fuzzy time series approaches for forecasting IT project cost [J].

Cheng, Ching-Hsue ;

Chang, Jing-Rong ;

Yeh, Che-An .

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2006, 73 (05) :524-542

[4] Some convergence results for probabilistic Tabu Search [J].

Faigle, Ulrich ;

Kern, Walter .

ORSA journal on computing, 1992, 4 (01) :32-37

[5]

Fox B. L., 1993, Annals of Operations Research, V41, P47, DOI 10.1007/BF02022562

[6]

GLOVER F, 1992, COMMUNICATION

[7] A note on fuzzy time-series model [J].

Hong, DH .

FUZZY SETS AND SYSTEMS, 2005, 155 (02) :309-316

[8] Heuristic models of fuzzy time series for forecasting [J].

Huarng, K .

FUZZY SETS AND SYSTEMS, 2001, 123 (03) :369-386

[9] Effective lengths of intervals to improve forecasting in fuzzy time series [J].

Huarng, K .

FUZZY SETS AND SYSTEMS, 2001, 123 (03) :387-394

[10] Ratio-based lengths of intervals to improve fuzzy time series forecasting [J].

Huarng, Kunhuang ;

Yu, Tiffany Hui-Kuang .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2006, 36 (02) :328-340

← 1 2 3 →