Một số phương pháp nâng cao độ chính xác dự báo trong mô hình chuỗi thời gian mờ

Tài liệu tham khảo

Loại

Chi tiết

[1] G Box, G Jenkins, Time series analysis: forecasting and control, New Jersey:Prentice-Hall, 1976

Khác

[2] R F Engle, Autoregressive conditional heteroscedasticity with estimator of the variance of United Kingdom inflation, Econ , 1982, 50, 987-1008

Khác

[3] T Bollerslev, Generalized autoregressive conditional heteroscedasticity J Econ , 1986, 31, 307-327

Khác

[4] F G Donaldson and M Kamstra, Forecast Combining with Neural Networks, Journal of forecasting, 1996, 15, 49-61

Khác

[5] J V Hansen, D N Ray, Neural Networks and Traditional Time Series Methods, A Synergistic Combination in State Economic Forecasts, 1997, 8(4), 863-873 [6] J S R Jang, ANFIS: adaptive network-based fuzzy inference systems IEEETrans Sys Man Cybern, 1993, 23, 665–685

Khác

[8] Q Song, B S Chissom, Forecasting enrolments with fuzzy time series - Part I, Fuzzy Sets and Systems, 1993a, 54(1),1-9

Khác

[9] Q Song, B S Chissom, Fuzzy time series and its models, Fuzzy Sets and Systems, 1993b, 4 (3), 269-277

Khác

[10] S M Chen, Forecasting Enrolments based on Fuzzy Time Series, Fuzzy set and systems, 1996, 81(3), 311-319

Khác

[11] K Huarng, Effective lengths of intervals to improve forecasting in fuzzy time sries, Fuzzy Sets and Systems, 2001b, 123(3), 387-394

Khác

[12] H K Yu, A refined fuzzy time-series model for forecasting, Physical A:Statistical Mechanics and Its Applications, 2005, 346 (3-4), pp 657-681 [13] H K Yu, Weighted fuzzy time series models for TAIEX forecasting Phys A:Stat Mech Appl, 2005, 349 (3–4), 609-624

Khác

[14] M Bose, K Mali, A novel data partitioning and rule selection technique for modeling high-order fuzzy time series Applied Soft Computing, 2017, 63(17), pp 87–96, doi: 10 1016/j asoc 2017 11 011

Khác

[15] S M Chen and N Y Chung, Forecasting enrolments of students by using fuzzy time series and genetic algorithms International Journal of Intelligent Systems, 2006a, 17, pp 1–17

Khác

[16] S M Chen, N Y Chung, Forecasting enrolments using high-order fuzzy time series and genetic algorithms International Journal of Intelligent Systems, 2006b, 21, 485–501

Khác

[17] S M Chen, K Tanuwijaya, Fuzzy forecasting based on high-order fuzzy logical relationships and automatic clustering techniques Expert Systems withApplications, 2011, 38, 15425–15437

Khác

[18] I H Kuo, et al, an improved method for forecasting enrolments based on fuzzy time series and particle swarm optimization Expert systems with applications, 2009, 36, 6108 – 6117

Khác

[19] H Tung, N D Thuan, V M Loc, The partitioning method based on hedge algebras for fuzzy time series forecasting”, Journal of Science and Technology, 2016, 54 (5), pp 571-583

Khác

[20] V M Loc, P T Yen P, P T H Nghia, Time Series Forecasting Using Fuzzy Time Series with Hedge Algebras Approach International Journal of Emerging Technology and Advanced Engineering), 2017, 7(12), 125-133

Khác

[21] W Lu, et al, using interval information granules to improve forecasting in fuzzy time series International Journal of Approximate Reasoning, 2015, 57, pp 1–18

Khác

[22] U Yolcu, E Egrioglu, V R Uslu, M A Basaran, C H Aladag, A New Approach for Determining the Length of Intervals for Fuzzy Time Series Applied Soft Computing 2009, 9, 647-651

Khác

[23] N Güler Dincer, Q Akkuş, A new fuzzy time series model based on robust clustering for forecasting of air pollution, Ecol Inform, 2018, 43, 157–164, http://dx doi org/10 1016/j ecoinf 2017 12 001

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Tiêu đề	Một Số Phương Pháp Nâng Cao Độ Chính Xác Dự Báo Trong Mô Hình Chuỗi Thời Gian Mờ
Người hướng dẫn	TS. Hà Nội
Trường học	Học viện Khoa học và Công nghệ
Chuyên ngành	Khoa học máy tính
Thể loại	luận án tiến sĩ
Năm xuất bản	2022
Thành phố	Hà Nội

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Số trang	133
Dung lượng	3,59 MB

Một số phương pháp nâng cao độ chính xác dự báo trong mô hình chuỗi thời gian mờ

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