Enhancing the Effectiveness of Forecasting the Foreign Exchange Reserves in Egypt, Using an Adaptive NeuroFuzzy Inference System | ||||
| The Egyptian Statistical Journal | ||||
| Article 4, Volume 58, Issue 2, December 2014, Page 171-182 PDF (7.78 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.2014.314447 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Rania Ahmed Hamed Mohamed | ||||
| port said university | ||||
| Abstract | ||||
| The foreign exchange reserves play an important role in Egyptian economy among other resources. The objective of the paper is to elaborate on enhancing the Effectiveness of Forecasting the Foreign Exchange Reserves in Egypt using Adaptive Neuro Fuzzy Inference System (ANFIS) as an alternative approach to regression analysis. Quarterly data used concern Suez Canal revenues; workers abroad remittances; exports; tourism revenues and foreign direct investment in Egypt. The data have been used as inputs to the model. ANFIS is one of the most successful approaches which combine the benefits of Artificial Neural Network (ANN) and Fuzzy Logic System (FLS) into a single framework. ANFIS incorporates self-learning ability of (ANN) with the linguistic expression function of fuzzy inference. The experimental results demonstrate that the ANFIS can be successfully applied and provides high accuracy in forecasting the foreign exchange reserves, compared to the regression model. | ||||
| Keywords | ||||
| Adaptive NeuroFuzzy Inference System; Artificial Neural Network; Fuzzy Logic Systems; and Regression Analysis | ||||
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