Higher order multivariate Markov chain model for fuzzy time series

被引：11
|
作者：
Suresh, S. [1 ]
Kannan, K. Senthamarai [2 ]
Venkatesan, P. [3 ]
机构：
[1] Univ Madras, Dept Stat, Madras 5, Tamil Nadu, India
[2] Manonmaniam Sundaranar Univ, Dept Stat, Tirunelveli, Tamil Nadu, India
[3] ICMR, Natl Inst Res TB, Dept Stat, Madras, Tamil Nadu, India
来源：
JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS | 2016年 / 19卷 / 01期
关键词：
Fuzzy sets; Markov model; Higher order Markov model; Linear programming problem and simulation;
D O I：
10.1080/09720510.2014.894303
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Time series analysis is often related with the discovery of patterns and prediction of features. In this paper, multivariate Markov model in fuzzy time series method to allow multi factor forecasting problem is proposed. An attempt is made to forecast global surface temperature with presence of CO2 emission. The computation is carried out using fuzzy sets and transition probability vectors. A time series model has been determined by applying Fuzzy logic. Reliability of the randomness of the forecast values have been studied by implementing random number simulation technique. Numerical computations have been carried out in support of theoretical findings.
引用
收藏
页码：21 / 35
页数：15
相关论文
共 50 条
  • [21] A multivariate heuristic model for fuzzy time-series forecasting
    Huarng, Kun-Huang
    Yu, Tiffany Hui-Kuang
    Hsu, Yu Wei
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2007, 37 (04): : 836 - 846
  • [22] Higher-order multivariate Markov chains and their applications
    Ching, Wai-Ki
    Ng, Michael K.
    Fung, Eric S.
    [J]. LINEAR ALGEBRA AND ITS APPLICATIONS, 2008, 428 (2-3) : 492 - 507
  • [23] A wind speed time series model based on advanced first-order markov chain approach
    [J]. Jiang, Ping, 1600, Automation of Electric Power Systems Press (38):
  • [24] Jakarta Composite Index Prediction Using Fuzzy Time Series Markov Chain
    Rachmawati, R. N.
    Gamalita, A.
    Sungkawa, I.
    [J]. INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2015, 53 (02): : 119 - 131
  • [25] Fuzzy Hidden Markov Chain Based Models for Time-Series Data
    Tao, Yihui
    Mahfouf, Mahdi
    [J]. ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS, UKCI 2022, 2024, 1454 : 13 - 23
  • [26] Comparison of Weighted Markov Chain and Fuzzy Time Series Markov Chain in Forecasting Stock Closing Price of Company X
    Kafi, R. A.
    Safitri, Y. R.
    Widyaningsih, Y.
    Handari, B. D.
    [J]. PROCEEDINGS OF THE 4TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES (ISCPMS2018), 2019, 2168
  • [27] Number of Overlapping Runs Until a Stopping Time for Higher Order Markov Chain
    Anuradha
    [J]. STATISTICS AND APPLICATIONS, 2023, 21 (02): : 261 - 280
  • [28] Multivariate High Order Fuzzy Time Series Forecasting for Car Road Accidents
    Jilani, Tahseen A.
    Burney, S. M. Aqil
    Ardil, C.
    [J]. PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 19, 2007, 19 : 288 - +
  • [29] A hidden Markov model-based forecasting model for fuzzy time series
    Institute of Information Management, National Cheng Kung University, Tainan, Taiwan
    不详
    不详
    [J]. WSEAS Trans. Syst., 2006, 8 (1919-1924):
  • [30] Fuzzy Time Series Forecasting With a Probabilistic Smoothing Hidden Markov Model
    Cheng, Yi-Chung
    Li, Sheng-Tun
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2012, 20 (02) : 291 - 304
12345