GLSSVM elevation fitting model optimized by fruit fly optimization algorithm

Aiming at the limitation of random parameter selection in least squares support vector machine (LSSVM) elevation fitting models, the fruit fly optimization algorithm (FOA) is introduced into the grey least square support vector machine (GLSSVM) elevation fitting model, then a GLSSVM fitting model based on FOA was established. In order to verify the validity of the proposed model, a case study is carried out and compared with GLSSVM and LSSVM. The results show that the proposed model converges faster and has higher accuracy, which provides a new approach for GNSS elevation fitting.