PREDICTION OF WAVE AND CURRENT FORCES ON SLENDER STRUCTURES IN THE FORM OF TIME SERIES USING ARTIFICIAL 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.

SHAFIEIFAR M.; MOGHIM M.N.

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

Journal Paper

Paper Information

Journal: JOURNAL OF MARINE ENGINEERING Year:2005 | Volume:1 | Issue:2 Page(s): 11-21

Download Full-Text

Persian Verion

View:

977

Download:

Cites:

Information Journal Paper

Title

PREDICTION OF WAVE AND CURRENT FORCES ON SLENDER STRUCTURES IN THE FORM OF TIME SERIES USING ARTIFICIAL NEURAL NETWORKS

Author(s)

SHAFIEIFAR M. | MOGHIM M.N. | Issue Writer Certificate

Keywords

OFFSHORE STRUCTURESQ4

SLENDER CYLINDERSQ4

WAVE FORCEQ3

CURRENTQ3

MORISON EQUATIONQ4

ARTIFICIAL NEURAL NETWORKSQ3

SUPERVISED LEARNINGQ4

Abstract

One of the most important issues in designing coastal and OFFSHORE STRUCTURES is the prediction of wave and CURRENT forces on SLENDER CYLINDERS. Such forces are often considered as dominate loadings. Many analytical and empirical methods such as MORISON EQUATION have been suggested for estimation of waves and CURRENT forces. Such methods, however, have shown inaccuracies in predicting hydrodynamic forces. On the other hand, ARTIFICIAL NEURAL NETWORKS (ANNs) have received a great deal of attention in recent years and are being touted as one of the greatest computational tools ever developed. In fact, ANNs are nonlinear systems consisting of a large number of highly interconnected processing units, nodes or artificial neurons, which have the ability of learning. In this research, ANNs have been used to estimate wave and CURRENT forces on SLENDER CYLINDERS. Data of 308 experimental specimens have been used for training and testing the networks. Considering the aim of this research for the application of ANNs, these data were consisted of recorded force values in different time series. The SUPERVISED LEARNING neural networks models have been used in this research. The results indicate the success of the application of neural networks approach which can efficiently predict waves and CURRENT forces on SLENDER CYLINDERS after carrying out appropriate training. Furthermore, the results are within acceptable accuracy in comparison with experimental results and the results obtained from MORISON EQUATION.

Cites

No record.

References

No record.

Cite

APA: Copy

SHAFIEIFAR, M., & MOGHIM, M.N.. (2005). PREDICTION OF WAVE AND CURRENT FORCES ON SLENDER STRUCTURES IN THE FORM OF TIME SERIES USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF MARINE ENGINEERING, 1(2), 11-21. SID. https://sid.ir/paper/60995/en

Vancouver: Copy

SHAFIEIFAR M., MOGHIM M.N.. PREDICTION OF WAVE AND CURRENT FORCES ON SLENDER STRUCTURES IN THE FORM OF TIME SERIES USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF MARINE ENGINEERING[Internet]. 2005;1(2):11-21. Available from: https://sid.ir/paper/60995/en

IEEE: Copy

M. SHAFIEIFAR, and M.N. MOGHIM, “PREDICTION OF WAVE AND CURRENT FORCES ON SLENDER STRUCTURES IN THE FORM OF TIME SERIES USING ARTIFICIAL NEURAL NETWORKS,” JOURNAL OF MARINE ENGINEERING, vol. 1, no. 2, pp. 11–21, 2005, [Online]. Available: https://sid.ir/paper/60995/en

Related Journal Papers