scholarly journals Microgrid Trading Game Model Based on Blockchain Technology and Optimized Particle Swarm Algorithm

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Binyao Liu ◽  
Ming Wang ◽  
Jiakai Men ◽  
Dechang Yang
Keyword(s):  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Game Model ◽  
Model Based ◽  
Blockchain Technology ◽  
Swarm Algorithm

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.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

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