A Comparative Analysis of Time Series Prediction Techniques a Systematic Literature Review (SLR)

This paper highlights the significance of systematic literature reviews and explores the different techniques employed in these reviews, including statistical methods, machine learning, deep learning, and hybrid methods. The study aims to understand the performance and effectiveness of these techniques in the context of literature reviews. Statistical methods offer quantitative insights and analysis, while machine learning and deep learning techniques enable automation and uncover complex patterns in large volumes of data. However, hybrid methods, which integrate multiple techniques, have shown superior performance in systematic literature reviews, combining the strengths of different methodologies to achieve more comprehensive and accurate outcomes. Further development and refinement of hybrid methods can enhance the quality and effectiveness of literature review processes.