ESTIMATION OF INVERSE DYNAMIC BEHAVIOR OF MR DAMPERS USING ARTIFICIAL AND FUZZY-BASED NEURAL NETWORKS

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.

GHASEMI M.R.; BARGHI E.

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

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING Year:2012 | Volume:2 | Issue:3 Page(s): 357-368

Download Full-Text

View:

329

Download:

184

Cites:

Information Journal Paper

Title

ESTIMATION OF INVERSE DYNAMIC BEHAVIOR OF MR DAMPERS USING ARTIFICIAL AND FUZZY-BASED NEURAL NETWORKS

Author(s)

GHASEMI M.R. | BARGHI E. | Issue Writer Certificate

Keywords

INVERSE DYNAMIC BEHAVIOR OF MR DAMPER

BACK PROPAGATION NEURAL NETWORKS

RADIAL BASIS FUNCTION NEURAL NETWORKS

ANFIS

MODIFIED BOUC-WEN MODEL

Abstract

In this paper the performance of Artificial Neural Networks (ANNs) and Adaptive Neuro- Fuzzy Inference Systems (ANFIS) in simulating the inverse dynamic behavior of Magneto- Rheological (MR) dampers is investigated. MR dampers are one of the most applicable methods in semi active control of seismic response of structures. Various mathematical models are introduced to simulate the dynamic behavior of MR dampers. The MODIFIED BOUC-WEN MODEL is an appropriate model that has an acceptable accuracy in calculating the generated force of dampers compared to others. In this model displacement and voltage of a MR damper are known while the force generated by MR damper is considered as the unknown. Because of highly nonlinear characteristics of MODIFIED BOUC-WEN MODEL determination of INVERSE DYNAMIC BEHAVIOR OF MR DAMPERs are generally done using ANNs and ANFIS. Since the ANNs and ANFIS have different mechanisms for emulating desired functions, their responses may be different. In this research the performance of a Back Propagation Neural Network (BPNN), Radial Basis Functions Neural Network (RBFNN) and ANFIS in estimating the INVERSE DYNAMIC BEHAVIOR OF MR DAMPERs are compared. The results emphasize on the advancement of ANFIS to the other methods studied in estimation of INVERSE DYNAMIC BEHAVIOR OF MR DAMPERs.

Cites

No record.

References

No record.

Cite

APA: Copy

GHASEMI, M.R., & BARGHI, E.. (2012). ESTIMATION OF INVERSE DYNAMIC BEHAVIOR OF MR DAMPERS USING ARTIFICIAL AND FUZZY-BASED NEURAL NETWORKS. INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING, 2(3), 357-368. SID. https://sid.ir/paper/329369/en

Vancouver: Copy

GHASEMI M.R., BARGHI E.. ESTIMATION OF INVERSE DYNAMIC BEHAVIOR OF MR DAMPERS USING ARTIFICIAL AND FUZZY-BASED NEURAL NETWORKS. INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING[Internet]. 2012;2(3):357-368. Available from: https://sid.ir/paper/329369/en

IEEE: Copy

M.R. GHASEMI, and E. BARGHI, “ESTIMATION OF INVERSE DYNAMIC BEHAVIOR OF MR DAMPERS USING ARTIFICIAL AND FUZZY-BASED NEURAL NETWORKS,” INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING, vol. 2, no. 3, pp. 357–368, 2012, [Online]. Available: https://sid.ir/paper/329369/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops