A hybrid fuzzy quantum time series and linear programming model: Special application on TAIEX index dataset

被引：9

作者：

Singh, Pritpal ^{[1
]}

Dhiman, Gaurav ^{[2
]}

Guo, Sen ^{[3
]}

Maini, Ritika ^{[4
]}

Kaur, Harsimran ^{[4
]}

Kaur, Amandeep ^{[2
]}

Kaur, Harmanpreet ^{[5
]}

Singh, Jaswinder ^{[6
]}

Singh, Napinder ^{[2
]}

机构：

[1] Smt Chandaben Mohanbhai Patel Inst Comp Applicat, CHARUSAT Campus Changa, Anand 388421, Gujarat, India

[2] Thapar Inst Engn & Technol, Comp Sci & Engn Dept, Patiala 147004, Punjab, India

[3] North China Elect Power Univ, Sch Econ & Management, Beijing 10206, Peoples R China

[4] Govt Bikram Coll Commerce, Dept Comp Sci, Patiala 147004, Punjab, India

[5] Texas Tech Univ, Plant & Soil Dept, Lubbock, TX 79409 USA

[6] Desh Bhagat Univ, Dept Comp Sci & Engn, Mandi Gobindgarh 147301, Punjab, India

来源：

MODERN PHYSICS LETTERS A | 2019年 / 34卷 / 25期

关键词：

Quantum; time series; logical relationships; intervals; SPOTTED HYENA OPTIMIZER; FORECASTING ENROLLMENTS; INFORMATION GRANULES; NEURAL-NETWORKS; ALGORITHM; SYNCHRONIZATION; SYSTEMS;

D O I：

10.1142/S0217732319502018

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

The supremacy of quantum approach is able to provide the solutions which are not practically feasible on classical machines. This paper introduces a novel quantum model for time series data which depends on the appropriate length of intervals. In this study, the effects of these drawbacks are elaborately illustrated, and some significant measures to remove them are suggested, such as use of degree of membership along with mid-value of the interval. All these improvements signify the effective results in case of quantum time series, which are verified and validated with real-time datasets.

引用

页数：20

共 50 条

[1] Hybrid Adaptive Fuzzy Time Series Model to Forecast TAIEX
Choua, Peng Szu
Liu, Jing-Wei
Cheng, Ching-Hsue
2012 8TH INTERNATIONAL CONFERENCE ON COMPUTING AND NETWORKING TECHNOLOGY (ICCNT, INC, ICCIS AND ICMIC), 2012, : 292 - 295
[2] A bivariate fuzzy time series model to forecast the TAIEX
Yu, Tiffany Hui-Kuang
Huarng, Kun-Huang
EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (04) : 2945 - 2952
[3] Prediction of TAIEX based on hybrid fuzzy time series model with single optimization process
Yolcu, Ozge Cagcag
Alpaslan, Faruk
APPLIED SOFT COMPUTING, 2018, 66 : 18 - 33
[4] An information criterion for fuzzy time series to forecast stock exchange index on TAIEX
Huarng, K
Yu, HK
PROCEEDINGS OF THE 7TH JOINT CONFERENCE ON INFORMATION SCIENCES, 2003, : 187 - 189
[5] Trend-weighted fuzzy time-series model for TAIEX forecasting
Cheng, Ching-Hsue
Chen, Tai-Liang
Chiang, Chen-Han
NEURAL INFORMATION PROCESSING, PT 3, PROCEEDINGS, 2006, 4234 : 469 - 477
[6] Fuzzy time-series based on adaptive expectation model for TAIEX forecasting
Cheng, Ching-Hsue
Chen, Tai-Liang
Teoh, Hia Jong
Chiang, Chen-Han
EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (02) : 1126 - 1132
[7] APPLICATIONS OF TAIEX AND ENROLLMENT FORECASTING USING AN EFFICIENT IMPROVED FUZZY TIME SERIES MODEL
Kuo, Shye- chorng
Lee, Chin-Ling
Lin, Cheng-Jian
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2016, 12 (02): : 459 - 466
[8] A bivariate fuzzy time series model to forecast the TAIEX (vol 34, pg 2945, 2010)
Yu, Tiffany Hui-Kuang
Huarng, Kun-Huang
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (07) : 5529 - 5529
[9] A Hybrid Model of Fuzzy time Series for Forecasting
Wang Jue
Qiao JianZhong
MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8, 2012, 433-440 : 2694 - 2698
[10] A Hybrid Fuzzy Time Series Model for Forecasting
Hassan, Saima
Jaafar, Jafreezal
Samir, Brahim B.
Jilani, Tahseen A.
ENGINEERING LETTERS, 2012, 20 (01) : 88 - 93

← 1 2 3 4 5 →