13 August، 2025
Master’s thesis by Raed Arif Snaan Abdullah
Discussion of the master’s thesis in the College of Computer Science and Mathematics -Department of Statistics and Informatics Department entitled: Using Echo State Network based on Bayesian Ridge Regression for Multivariate Time Series Forecasting
Master’s thesis by Raed Arif Snaan Abdullah
supervised by Assis.Prof.Dr. Osamah Basheer Shukur
This thesis includes the development of a hybrid model combining Echo State Network (ESN) and Bayesian Ridge Regression (BRR) based on the Ridge Regression(RR) model to forecast climate time series. It also examines the problem of nonlinearity and multicollinearity in climate data.
The study addresses the method of calculating the Variance Inflation Factor (VIF) to detect multicollinearity. It also examines how to improve forecasting accuracy using indices such as RMSE.
The study aims to develop a more accurate forecasting model for multivariate climate time series, combining the power of ESN in capturing nonlinear temporal patterns with the ability of BRR to address multicollinearity.
The discussion committee consists of
Professor Dr. Muthanna Subhi Sulaiman (Chairman)
Assis.Prof.Dr. Najlaa Saad Ibrahim (member)
Lecturer Mohammed Qasim Yahya (Member)
Assis.Prof.Dr. Osamah Basheer Shukur (member and supervisor)
