In the volatile sphere of copyright, portfolio optimization presents a formidable challenge. Traditional methods often fail to keep pace with the swift market shifts. However, machine learning models are emerging as a promising solution to enhance copyright portfolio performance. These algorithms interpret vast information sets to identify patterns