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Comparison Performance Prediction between some Artificial Neural Networks (Box Jenkins) methodology with application | ||
| IRAQI JOURNAL OF STATISTICAL SCIENCES | ||
| Article 3, Volume 16, Issue 1, 2019, Pages 51-76 PDF (1.42 M) | ||
| DOI: 10.33899/iqjoss.2019.0164183 | ||
| Authors | ||
| Rehad Shamany* ; Thafer Ramadan | ||
| Assistant Lecturer / Department of Statistics and Informatics / College of Computer Science and Mathematics / University of Mosul | ||
| Abstract | ||
| This paper compares a prediction accuracy between the statistical time series method that use (Box – Jenkins) methodology, and some artificial neural networks, which differ from them through the feedback in their structure. These networks are Feed Forward Neural Network (FFNN), Elman Neural Network (ENN), and Nonlinear Autoregressive with Exogenous Input (NARX). By using a set of data, the average monthly maximum temperatures in Mosul for the years (1983– 2009), which numbered 324 observations, twelve observations were kept as Truncated samples in order to compare with the results of prediction models for the above two methods. The results of prediction with performance of neural networks with feedback is better than others, and the performance methodology of (Box - Jenkins). | ||
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