Evaluation Of Sailing Boat Performance Based on Ridge Regression and Mathematical Model Optimization

Abstract

The traditional linear regression model can analyze and determine the coefficient between variables, reflecting the interpretation degree of variables in the equation. However, if the model is too complex, the training data is too few or too extreme, overfitting will occur, and the prediction effect of multicollinearity data is not good. The regularized ridge regression model can solve this problem. In this paper, Ridge regression analysis is carried out on the sailing performance data. Firstly, the data are preprocessed, and then the root-mean-square error RMSE=10.68 is obtained through the ridge regression model evaluation. The model fitting effect is good, and the regression coefficient corresponding to the variable Fr is the largest, indicating that the Froude number is the most obvious to the performance of the yacht. The variable beam draft ratio of B/Dr Is the least important to the yacht's performance. The conclusion of this paper can predict the performance of yachts more accurately, and provide corresponding improvement suggestions for enterprises.