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Research on Digital Economy of Intelligent Emergency Risk Avoidance in Sudden Financial Disasters Based on PSO-BPNN Algorithm

机译:基于PSO-BPNN算法的突发金融灾害智能应急风险规避数字经济研究

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摘要

In recent years, disasters have seriously affected the normal development of financial business in some regions. At the time of disaster, how to effectively integrate resources of all parties, deal with sudden financial disasters efficiently, and restore financial services in time has become an important task. Therefore, this paper adopts Particle Swarm Optimization (PSO) to improve the traditional BP Neural Network (BPNN) and finally constructs a Particle Swarm Optimization powered BP Neural Network (PSO-BPNN) model for the intelligent emergency risk avoidance of sudden financial disasters in digital economy. At the same time, the proposed algorithm is also compared to GA-BPNN and BPNN algorithms, which are also intelligent algorithms. Experimental results show that the hybrid PSO-BPNN algorithm is superior to GA-BPNN algorithm and BPNN algorithm in simulation and prediction effect. It can accurately predict the sudden financial disaster in recent period, so the model has a good application prospect.
机译:近年来,灾害严重影响了部分地区金融业务的正常发展。在灾难发生时,如何有效整合各方资源,高效应对突发金融灾害,及时恢复金融服务成为一项重要任务。因此,本文采用粒子群优化(PSO)对传统的BP神经网络(BPNN)进行改进,最终构建了基于粒子群优化的BP神经网络(PSO-BPNN)模型,用于数字经济中突发金融灾难的智能应急风险规避。同时,将所提算法与同样为智能算法的GA-BPNN和BPNN算法进行了对比。实验结果表明,混合PSO-BPNN算法在仿真和预测效果上优于GA-BPNN算法和BPNN算法。该模型能够准确预测近期突发的金融灾难,具有良好的应用前景。

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