where \(\omega\) and b are the parameter vectors. The kernel function\(K\left(x_{i},x_{j}\right)=\left\langle\varphi(x_{i})\bullet\varphi(x_{j})\right\rangle\)can be used to calculate the inner products in the feature space\(\Phi\). By introducing \({}_{i}\) and\({\overset{\overline{}}{\alpha}}_{i}\) in the dual form to solve the optimization problem in SVR, the regression function of the nonlinear SVR allowing the kernel function is expressed as: