A Subgrade Settlement Prediction Model Based on Improved Particle Swarm Neural Network

2020 ◽  
Author(s):  
Quan Bei ◽  
Lu Xuanmin
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Particle Swarm ◽  
Settlement Prediction ◽  
Model Based

CVaR Prediction Model of the Investment Portfolio Based on the Convolutional Neural Network Facilitates the Risk Management of the Financial Market

2022 ◽  
Vol 30 (7) ◽  
pp. 0-0
Keyword(s):  
Neural Network ◽  
Risk Management ◽  
Prediction Model ◽  
Convolutional Neural Network ◽  
Financial Market ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Investment Portfolio ◽  
Model Based ◽  
Swarm Algorithm

In summary, firstly, a method for establishing a portfolio model is proposed based on the risk management theory of the financial market. Then, a prediction model for CVaR is established based on the convolutional neural network, and the improved particle swarm algorithm is employed to solve the model. The actual data analysis is implemented to prove the feasibility of CVaR prediction model based on deep learning and particle swarm optimization algorithm in financial market risk management. The test results show that the investment portfolio CVaR prediction model based on the convolutional neural network can obtain the optimal solution in the 18th generation at the fastest after using the improved particle swarm algorithm, which is more effective than the traditional algorithm. The CVaR prediction model of the investment portfolio based on the convolutional neural network facilitates the risk management of the financial market.

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