التنبؤ بالسلاسل الزمنية بالاعتماد على النموذج الهجين للانحدار الذاتي والمتوسطات المتحركة التكاملية ونموذج انحدار متجه الدعم

Abstract EN

This paper using three models for predicting time series, auto regressive integrated moving average (ARIMA) model and the support vector regression and hybrid model by combining the arima mode with the SVR model, these models are used to predict monthly global gold prices, based on a time series of monthly global gold prices, the time series data was used during the period from Jan-1991-Dec-2021, to compare hybrid model of ARIMA-SVR with individual models ARIMA and SVR, these models are compared using the MSE, MAE and MAPE,T prediction accuracy measures to find the most appropriate model for predicting future values.

this paper reveals the superiority of ARIMA-SVR on other individual models by having the lowest values of the prediction measures.