The parameter selection method for support vector regression based on adaptive fusion of mixed kernel function Initialization: ( ) For original data set , select the mixed kernel function, and set the initial parameter state value . ( ) Divide into groups by using fold cross validation method denoted by . While (Parameter state value does not meet the set conditions) do Time update process: ( ) Calculate weights , , , using formulas (6 )-(7 ). Measurement update process: ( ) Decompose one step prediction error covariance matrix and evaluate the cubature point according to formula ( ) in reference [19 ]. ( ) Train the data set based on the LIBSVM algorithm to obtain the final prediction output. ( ) Combining predict , compute one step prediction by using formula (12 ). ( ) Use formula ( )–( ) of reference [19 ] to implement the subsequent measurement update. End while End