APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN ANALYSIS OF FLEXIBLE PAVEMENT STRUCTURE

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.

AMERI MAHMOUD; MOLAYEM M.

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

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN) Year:2007 | Volume:17 | Issue:5 Page(s): 53-60

Download Full-Text

Persian Verion

View:

1,973

Download:

Cites:

Information Journal Paper

Title

APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN ANALYSIS OF FLEXIBLE PAVEMENT STRUCTURE

Author(s)

AMERI MAHMOUD | MOLAYEM M. | Issue Writer Certificate

Keywords

Not Registered.

Abstract

The first step in pavement design process is evaluation of subgrade soil properties, material properties that are available at the job site and also estimating the probable traffic volume that will use the road. Using this information, several pavement structures are considered as alternatives. Economic comparison as well as constructability of these alternatives will lead to selection of final design. Structural analyses of these alternatives require an accredited soft ware that has capability of modeling pavement cross sections. Otherwise comparison of structural integrity of these alternatives will be cumbersome. At the present time there are several computer programs that are available for structural analyses of pavement cross sections. However, a lot of data input information is needed for adequate use of these programs. Under many circumstances these information are not readily available. Therefore many consulting engineers are reluctant to use these soft wares. For this reason in this paper it is proposed to employ Artificial Neural Networks (ANN) as a substitute for these soft wares. One of the advantages of using (ANN) is that they require less data input information for analysis of pavement structure. With (ANN) it is possible to analyze several pavement structures simultaneously. Another advantage of using ANN is that they are fast and can adapt to changes in data and learn the characteristics of input signals. The neural network proposed in this paper is known as multilayered, feed Back Propagation Neural Network (BPNN) of the type 5-4-4-2 that has the capability of analyzing pavement structure with fewer data input information.

Cites

No record.

References

No record.

Cite

APA: Copy

AMERI, MAHMOUD, & MOLAYEM, M.. (2007). APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN ANALYSIS OF FLEXIBLE PAVEMENT STRUCTURE. INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN), 17(5), 53-60. SID. https://sid.ir/paper/65808/en

Vancouver: Copy

AMERI MAHMOUD, MOLAYEM M.. APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN ANALYSIS OF FLEXIBLE PAVEMENT STRUCTURE. INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN)[Internet]. 2007;17(5):53-60. Available from: https://sid.ir/paper/65808/en

IEEE: Copy

MAHMOUD AMERI, and M. MOLAYEM, “APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN ANALYSIS OF FLEXIBLE PAVEMENT STRUCTURE,” INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN), vol. 17, no. 5, pp. 53–60, 2007, [Online]. Available: https://sid.ir/paper/65808/en

Related Journal Papers