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
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