Exploration of Intelligent Optimization Algorithm for Risk Management in Green Financial Market Driven by Science and Technology Innovation

Abstract

Green finance driven by science and technology innovation, as an innovative financial model, is facing problems such as weak risk management prediction ability while developing rapidly worldwide. Green finance driven by science and technology innovation, as an innovative financial model, is rapidly developing globally while it faces challenges such as insufficient incentive and constraint mechanisms and weak risk management prediction ability. Based on this, this paper introduces the IPSO-BP model for green finance market risk prediction model. The model uses BP neural network to process green financial market data, and introduces the IPSO algorithm to optimize the parameters of the BP network, aiming to enhance the model's prediction ability of green financial market risk. The results of the study on the actual dataset found that the prediction accuracy of the IPSO-BP model on the green financial market reached a maximum of 95.38%, and the absolute error of most of the prediction results is less than 0.06. Relying on the risk prediction results of the green financial market obtained by the IPSO-BP model, it can assist investors in choosing a more reasonable investment strategy, and ensure the stable operation of the green financial market at the same time, and enhance the risk control ability of investors. , and enhance the risk control ability of investors.