A Comparison between Fuzzy Inference Systems for Prediction (with Application to Prices of Fund in Egypt)
This paper outlines the basic differences between the Fuzzy logic techniques, including Mamdani , Sugeno fuzzy inference system models and Adaptive Neuro-Fuzzy Inference System (ANFIS) . The main motivation behind this research is to assess which approach provides the best performance for predicting...
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| Veröffentlicht in: | International journal of computer applications 2015-01, Vol.109 (13), p.6-11 |
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| container_title | International journal of computer applications |
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| creator | Fahmy, Raafat Zaher, Hegazy Kandil, Abd Elfattah |
| description | This paper outlines the basic differences between the Fuzzy logic techniques, including Mamdani , Sugeno fuzzy inference system models and Adaptive Neuro-Fuzzy Inference System (ANFIS) . The main motivation behind this research is to assess which approach provides the best performance for predicting prices of Fund. Due to the importance of performance in Economy, the Mamdani , Sugeno models and ANFIS are compared with the actual values. Fuzzy inference systems (Mamdani , Sugeno and ANFIS fuzzy models ) can be used to predict the weekly prices of Fund for the Egyptian Market. The application results indicate that (ANFIS) model is better than that of Mamdani and Sugeno . The results of the three fuzzy inference systems (FIS) are compared. |
| doi_str_mv | 10.5120/19246-0604 |
| format | Article |
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| language | eng |
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| source | EZB-FREE-00999 freely available EZB journals |
| subjects | Adaptive systems Artificial neural networks Economics Fuzzy Fuzzy logic Fuzzy set theory Inference Mathematical models |
| title | A Comparison between Fuzzy Inference Systems for Prediction (with Application to Prices of Fund in Egypt) |
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