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- W2978859770 abstract "In the welding quality,an important factor is the melting wide investigation.Welding process is a multi-factor strong coupling problem,in order to study the changes predicted weld width,we propose using support vector machine regression predicting weld width.Construct a support vector regression model,and the use of experimental data to verify its accuracy,the BP neural network as a means of comparison to test support vector regression to predict the effect of weld width.The results show that: in the training,single-step and multi-step prediction forecasting process,BP neural networks and support vector machines have applicability,can be very good for high-power laser welding process dish,but relative to the BP neural network concerned,SVR is more appropriate,and the two methods in the same number of steps,the support vector machine is better than BP neural network prediction error is more uniform,more small fluctuations.SVR in the optimal value of 3:00 to obtain N,N,but it will increase the value of the calculation to obtain a small amount of computation time,eventually a combination of various factors that the optimal N value is 10." @default.
- W2978859770 created "2019-10-10" @default.
- W2978859770 creator A5052917236 @default.
- W2978859770 date "2014-01-01" @default.
- W2978859770 modified "2023-09-24" @default.
- W2978859770 title "Welding weld width support vector regression prediction based on a mathematical model of high-power disc laser welding" @default.
- W2978859770 hasPublicationYear "2014" @default.
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