Research on a New Performance Evaluation Method for University Research Project Management

The performance evaluation of university research project management plays a crucial role in enhancing project management and promoting scientific research development. This study proposes an improved approach to enhance the accuracy of the BP neural network algorithm in project management performance evaluation by combining it with genetic algorithm. The proposed method incorporates genetic algorithm into the BP neural network to search for optimal initial network weights and thresholds, obtaining the optimal solution through training. To verify the feasibility of this method, we conducted a performance evaluation of the research project management at Chengyi College of Jimei University. The experimental results demonstrate that this method exhibits strong non-linear fitting capability and higher evaluation accuracy, making it suitable for evaluating the performance of university research project management. This research achievement provides an effective tool for enhancing the performance evaluation of university research project management, improving project management practices, and offering scientific and reliable decision-making basis for university management.