بحث علمي "لاستخدام نماذج الشبكات العصبية لتنبؤ بالسلاسل الزمنية" منشور في مجلة علمية

This study aimed to Performance Comparison of Neural Networks (MLP, RBFNN,

ERNN, JRNN) Models for the time series data of a monthly Stock Prices to Bank of

Palestine from Nov. 2005 to Oct. 2020, and comparing between models to see which

one is better in forecasting. The results of applying the methods were compared

through the (MAPE, MAE, RMSE), the most accurate model is ERNN 14-25-1 with

minimum forecast measure error.

تم استخدام الشبكات العصبية في التنبؤ بالسلاسل الزمنية