Importance Of Fuzzy Neural Networks In More Accurate Prediction Of Expected Activity Levels And Major Operational And Financial Trends (A Case Study: Sarkhoon&Geshm Gas Refinery Co.)

Journal Title: International Research Journal of Applied and Basic Sciences - Year 2013, Vol 6, Issue 3

Abstract

Identification of a series of products and activities and subsequent activity levels expected Ability to effectively plan sales and profit forecasts. Determining the optimal point to improve the company's production and Planning for the future managers will be important to maximize the organization's goals.With increasing advances in science, the use of new techniques and the use of intelligent technology boom have been predicted in. The prediction methods, artificial neural networks and fuzzy logic have been applied in many fields and each one has its advantages and disadvantages. In this paper, the application of science to predict the expected levels and trends in key financial and operational activities of the SarkhoonandQeshm Gas Refinerycompany is used for the study. The design and implementation of Fuzzy Neural Network Model, Using four criteria of measurement error, Model results are compared only with the ANN model, The results show that the fuzzy neural model predictions are much better And the higher the speed and the ability of single neural network to predict has been a stronger approximation .

Authors and Affiliations

FaribaBordbar*| MSc in Accounting, Master of university, Zahedan, Iran, Mohammad Omidvar| MSc in Information Technology, Head of IT Projects, Sarkhoon and Qeshm Inc., Bandar Abbas, Iran

Keywords

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  • EP ID EP6136
  • DOI -
  • Views 273
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How To Cite

FaribaBordbar*, Mohammad Omidvar (2013). Importance Of Fuzzy Neural Networks In More Accurate Prediction Of Expected Activity Levels And Major Operational And Financial Trends (A Case Study: Sarkhoon&Geshm Gas Refinery Co.). International Research Journal of Applied and Basic Sciences, 6(3), 359-367. https://europub.co.uk/articles/-A-6136