REVIEW OF ARTIFICIAL NEURAL NETWORKS PERFORMANCE IN PREDICTING INTELLECTUAL CAPITAL EFFICIENCY OF ACCEPTED COMPANIES IN TEHRAN STOCK EXCHANGE (CASE STUDY: AUTOMOBILE INDUSTRY AND COMPONENTS MANUFACTURING COMPANIES)

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.

FAZEL YAZDI A.; MEHRJARDI R.T.; TAHARI MEHRJARDI M.H.

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

Journal Paper

Paper Information

Journal: FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT) Year:2013 | Volume:4 | Issue:16 Page(s): 127-153

Download Full-Text

Persian Verion

View:

1,353

Download:

Cites:

Information Journal Paper

Title

REVIEW OF ARTIFICIAL NEURAL NETWORKS PERFORMANCE IN PREDICTING INTELLECTUAL CAPITAL EFFICIENCY OF ACCEPTED COMPANIES IN TEHRAN STOCK EXCHANGE (CASE STUDY: AUTOMOBILE INDUSTRY AND COMPONENTS MANUFACTURING COMPANIES)

Author(s)

FAZEL YAZDI A. | MEHRJARDI R.T. | TAHARI MEHRJARDI M.H. | Issue Writer Certificate

Keywords

INTELLECTUAL CAPITALQ2

DEAQ2

ARTIFICIAL NEURAL NETWORKSQ2

Abstract

INTELLECTUAL CAPITAL is known as a real capital and one of the most important assets of organizations. The purpose of this study was to evaluate the performance of ARTIFICIAL NEURAL NETWORKS in predicting INTELLECTUAL CAPITAL efficiency in Accepted Companies in Tehran Stock Exchange. First, by using DEA Model and considering the value added coefficient variable of INTELLECTUAL CAPITAL as a model input, and three variables including stock return, return on assets and return on equity as a model output variables, INTELLECTUAL CAPITAL efficiency of selected companies between 1385 to 1389 were investigated. At next step, multilayer Perceptron Neural Network Approach is used to predicting INTELLECTUAL CAPITAL efficiency in companies. The results showed that Artificial Neural Network Model have high accuracy in predicting INTELLECTUAL CAPITAL efficiency of accepted companies in Tehran Stock Exchange.

Cites

No record.

References

Cite

APA: Copy

FAZEL YAZDI, A., MEHRJARDI, R.T., & TAHARI MEHRJARDI, M.H.. (2013). REVIEW OF ARTIFICIAL NEURAL NETWORKS PERFORMANCE IN PREDICTING INTELLECTUAL CAPITAL EFFICIENCY OF ACCEPTED COMPANIES IN TEHRAN STOCK EXCHANGE (CASE STUDY: AUTOMOBILE INDUSTRY AND COMPONENTS MANUFACTURING COMPANIES). FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), 4(16), 127-153. SID. https://sid.ir/paper/197550/en

Vancouver: Copy

FAZEL YAZDI A., MEHRJARDI R.T., TAHARI MEHRJARDI M.H.. REVIEW OF ARTIFICIAL NEURAL NETWORKS PERFORMANCE IN PREDICTING INTELLECTUAL CAPITAL EFFICIENCY OF ACCEPTED COMPANIES IN TEHRAN STOCK EXCHANGE (CASE STUDY: AUTOMOBILE INDUSTRY AND COMPONENTS MANUFACTURING COMPANIES). FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)[Internet]. 2013;4(16):127-153. Available from: https://sid.ir/paper/197550/en

IEEE: Copy

A. FAZEL YAZDI, R.T. MEHRJARDI, and M.H. TAHARI MEHRJARDI, “REVIEW OF ARTIFICIAL NEURAL NETWORKS PERFORMANCE IN PREDICTING INTELLECTUAL CAPITAL EFFICIENCY OF ACCEPTED COMPANIES IN TEHRAN STOCK EXCHANGE (CASE STUDY: AUTOMOBILE INDUSTRY AND COMPONENTS MANUFACTURING COMPANIES),” FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), vol. 4, no. 16, pp. 127–153, 2013, [Online]. Available: https://sid.ir/paper/197550/en

Related Journal Papers