A support vector machine（ SVM） model based on artificial bee colony（ ABC） and particle swarm hybrid optimization algorithm is proposed to have a correction for the measurement of infrared methane sensor aiming at in industrial field which is easy to be affected by temperature

humidity and other gases

and so on. The model combines the ABC algorithm with the PSO algorithm to form a hybrid optimization algorithm. It can detect the change of non target variables

and quickly and accurately search the SVM parameters. In experiments

adopting infrared methane sensor to measure concentration of 16 groups of standard methane gas which is in the range of0 %

5. 05 %. Selecting 11 groups of data as

training set and the rest of data as test set to establish ε-SVM regression correction model and carry out prediction. The results show that regression fitting effect of the model is good

and the prediction precision is higher than single optimization algorithm of SVM model.