Research on Financial Risk Prediction Method Based on Multi-Objective Computer Deep Learning Model

This paper presents a multi-objective deep learning model for financial risk prediction. The research aims to address the limitations of traditional methods by introducing a deep learning model that optimizes multiple financial risk targets simultaneously, improving both the accuracy and robustness of the prediction. We first preprocess financial data and select representative financial features as inputs. Then, we design a multi-objective deep learning model that integrates multi-objective optimization algorithms to optimize multiple risk prediction targets. Experimental results show that the proposed method significantly outperforms traditional financial risk prediction models in terms of accuracy and stability. Finally, we discuss the strengths and limitations of the model and suggest future improvements and research directions.