CHAOTIC TIME SERIES PREDICTION BY AUTO FUZZY REGRESSION MODEL

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

NAZARI HALEH; MOTAMENI HOMAYON; SHIRAZI BABAK

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF ADVANCES IN COMPUTER RESEARCH Year:2014 | Volume:5 | Issue:2 (16) Page(s): 45-50

Download Full-Text

View:

325

Download:

Cites:

Information Journal Paper

Title

CHAOTIC TIME SERIES PREDICTION BY AUTO FUZZY REGRESSION MODEL

Author(s)

NAZARI HALEH | MOTAMENI HOMAYON | SHIRAZI BABAK | Issue Writer Certificate

Keywords

FUZZY TECHNIQUES

STATISTICAL TECHNIQUES

CHAOTIC TIME SERIES

PREDICTION

REGRESSION

Abstract

Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and Chissom introduced the concept of fuzzy time series and applied some methods to the enrolments of the University of Alabama. Thereafter we apply FUZZY TECHNIQUES for system identification and apply STATISTICAL TECHNIQUES to modelling system. An automatic methodology framework that combines FUZZY TECHNIQUES and STATISTICAL TECHNIQUES for nonparametric residual variance estimation is proposed. The methodology framework is creating REGRESSION model by using FUZZY TECHNIQUES. Identification is performed through learning from examples method introduced by Wang and Mendel algorithm. Delta test residual noise estimation is used in order to select the best subset of inputs as well as the number of linguistic labels for the inputs. An experimental result for CHAOTIC TIME SERIES PREDICTION is compared with statistical model and shows the advantages of the proposed methodology in terms of approximation accuracy, generalization capability and linguistic interpretability.

Cites

No record.

References

Cite

APA: Copy

NAZARI, HALEH, MOTAMENI, HOMAYON, & SHIRAZI, BABAK. (2014). CHAOTIC TIME SERIES PREDICTION BY AUTO FUZZY REGRESSION MODEL. JOURNAL OF ADVANCES IN COMPUTER RESEARCH, 5(2 (16)), 45-50. SID. https://sid.ir/paper/328759/en

Vancouver: Copy

NAZARI HALEH, MOTAMENI HOMAYON, SHIRAZI BABAK. CHAOTIC TIME SERIES PREDICTION BY AUTO FUZZY REGRESSION MODEL. JOURNAL OF ADVANCES IN COMPUTER RESEARCH[Internet]. 2014;5(2 (16)):45-50. Available from: https://sid.ir/paper/328759/en

IEEE: Copy

HALEH NAZARI, HOMAYON MOTAMENI, and BABAK SHIRAZI, “CHAOTIC TIME SERIES PREDICTION BY AUTO FUZZY REGRESSION MODEL,” JOURNAL OF ADVANCES IN COMPUTER RESEARCH, vol. 5, no. 2 (16), pp. 45–50, 2014, [Online]. Available: https://sid.ir/paper/328759/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops