Optimization study of wind pressure sensor based on MSSA-SVR
JIA Peng
WANG Rui
Abstract：In response to the temperature drift phenomenon of wind pressure sensors,the support vec-tor regression model(SVR)is used to compensate for temperature,and the sparrow search algorithm in swarm intelligence algorithm is used for parameter selection.Due to the significant impact of kernel function parameter selection on the prediction effect of SVR,the cubic chaos mapping algorithm(MSSA)is introduced for multi strategy improvement.Based on the MSSA-SVR tempera-ture compensation algorithm experiment,it is found that by the 29th iteration of the temperature compensation algorithm,the predicted value after temperature compensation has basically overlapped with the actual value,and the prediction error is controlled within 0.01,which meets the temperature compensation requirements of Xishan Coal and Electricity.
Keywords：MSSA-SVRwind pressure sensortemperature compensationsparrow search algorithmal-gorithm optimization
Publication Date：2025-06-15
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 31-36 )