全球定位系统2025，Vol.50Issue(1)：69-72,4.DOI:10.12265/j.gnss.2024059
果蝇算法优化的GLSSVM高程拟合模型
GLSSVM elevation fitting model optimized by fruit fly optimization algorithm
摘要
Abstract
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.关键词
最小二乘支持向量机(LSSVM)/果蝇优化算法(FOA)/GNSS高程拟合/模型优化Key words
least square support vector machine(LSSVM)/fruit fly optimization algorithm(FOA)/GNSS elevation fitting/model optimization分类
测绘与仪器引用本文复制引用
谢洋洋..果蝇算法优化的GLSSVM高程拟合模型[J].全球定位系统,2025,50(1):69-72,4.基金项目
江苏省自然资源科技计划项目(2023008) （2023008）
