Algorithm Research on Investment and Financing Decision Support System Based on Deep Learning
Zuo Peiwen, Qian Liu, Ning Zhang · 2025
This study proposes an investment and financing decision support system based on deep learning and transfer learning algorithms. By combining the transfer learning algorithm with the deep learning algorithm, the system can transfer knowledge between different fields, thereby improving the adaptability and generalization ability of the model. The study first extracted features and preprocessed data for key variables in investment and financing decisions, trained them using deep learning models, and designed an optimized transfer learning algorithm in the system to cope with data scarcity or imbalance. By building an investment and financing decision support system, intelligent investment and financing decision analysis and suggestions are provided. The system simulation part evaluates the model performance through multiple groups of experiments. The results show that the system performs well in accuracy, robustness, and decision-making efficiency. The data analysis in the simulation results shows that the system combined with the transfer learning algorithm can effectively reduce overfitting and improve the accuracy of prediction. This study provides an efficient and intelligent decision support tool for the field of investment and financing, and has strong practicality and expansibility.