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- W3216034258 abstract "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." @default.
- W3216034258 created "2021-12-06" @default.
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- W3216034258 date "2021-11-30" @default.
- W3216034258 modified "2023-10-16" @default.
- W3216034258 title "Research on Digital Economy of Intelligent Emergency Risk Avoidance in Sudden Financial Disasters Based on PSO-BPNN Algorithm" @default.
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- W3216034258 doi "https://doi.org/10.1155/2021/7708422" @default.
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