FORECASTING PETROLEUM PRODUCTION USING CHAOS TIME SERIES ANALYSIS AND FUZZY CLUSTERING
Journal: ICTACT Journal on Soft Computing (IJSC) (Vol.4, No. 4)Publication Date: 2014-07-01
Authors : K. I. Jabbarova; O. H. Huseynov;
Page : 791-795
Keywords : Chaos; Lyapunov Exponents; Embedding Dimension; Petroleum Production; Fuzzy “IF-THEN” Rules;
Abstract
Forecasting of petroleum production time series is a key task underlying scheduling of oil refinery production. In turn, forecasting requires analysing whether time series exhibits chaotic behavior. In this paper we consider chaos analysis based forecasting of time series of gasoline and diesel production. Chaos analysis is based on Lyapunov exponents and includes determination of optimal values of embedding dimension and time lag by using differential entropy approach. For forecasting of petroleum production, fuzzy “IF-THEN” rules constructed on the base of fuzzy clustering of the time series are used. The obtained prediction results show adequacy of the used methodology.
Other Latest Articles
- COLLABORATIVE NETWORK SECURITY MANAGEMENT SYSTEM BASED ON ASSOCIATION MINING RULE
- ASSESSMENT OF PERFORMANCES OF VARIOUS MACHINE LEARNING ALGORITHMS DURING AUTOMATED EVALUATION OF DESCRIPTIVE ANSWERS
- Self-attitude structure of the students as a component of determinant system of the personal maturity formation
- Temporal characteristics of metacognitive competence of high school teachers
- Psychological content of the mid-life crisis of personality
Last modified: 2014-09-02 13:46:32