Probing efficiency scale of fuzzy neural network on forecasting stock exchange of the automobile industries in Iran

Ali Sorayaei; M  R  Salimi  and Masoumeh Seifi Divkolaii

doi:10.17485/ijst/2012/v5i4.17

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Probing efficiency scale of fuzzy neural network on forecasting stock exchange of the automobile industries in Iran

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2012/v5i4.17

Year: 2012, Volume: 5, Issue: 4, Pages: 1-3

Original Article

Probing efficiency scale of fuzzy neural network on forecasting stock exchange of the automobile industries in Iran

Ali Sorayaei ^*1, M. R. Salimi² and Masoumeh Seifi Divkolaii³

¹Faculty of Management, Babol Branch,
²Department of Computer Engineering,
³Member of Young Researchers Club of Qaemshahr, [email protected]*1
[email protected]³*Athour For Correspondence
Ali Sorayaei
Department of Computer Engineering
Email:[email protected]*1

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

There are several approaches to the treatment of predicting the risk of invest in stock exchange. In this paper we presented fuzzy network model in the base of data from Iranian stock exchange organization and then we compare our results with other models to forecast the stock value of main automobile industries in Iran. This method is not only precise and simple, but also intelligent, with the predicted results well agreeing with the practical conditions. Therefore, this method can be applied to the relevant financial investigation projects both institutionally and personally with satisfactory results but indicate the bubble growth of stock exchange of Iran automobile industries.
Keywords: Stock exchange; Fuzzy neural network; Automobile industry