2021/02/15 by Amirehsan Ghasemi, Ghasemi, Amirehsan, Kelvin J. Msechu +11
Computer Science · Engineering · Environmental Science · Mathematics · #3D Modeling in Geospatial Applications #Algorithm #Applied mathematics #Artificial intelligence #Basis (linear algebra) #Computer science #Convergence (economics) #Delaunay triangulation #Engineering #FOS: Computer and information sciences #FOS: Mathematics #Function (biology) #Geometry #Hydrology and Watershed Management Studies #Interpolation (computer graphics) #Machine Learning (cs.LG) #Mathematical optimization #Mathematics #Numerical Analysis (math.NA) #Radial basis function #Range (aeronautics) #Soil Geostatistics and Mapping #cs.LG #cs.NA #math.NA
paper · pdf · doi:10.48550/arxiv.2102.07890
openalex publication_date 2021/02/15 · arxiv created 2021/03/19 · arxiv updated 2021/03/23 · openalex created_date 2021/03/29 · openalex updated_date 2026/07/28
In this paper, the accuracy of two mesh-free approximation approaches, the Gravity model and Radial Basis Function, are compared. The two schemes' convergence behaviors prove that RBF is faster and more accurate than the Gravity model. As a case study, the interpolation of temperature at different locations in Tennesse, USA, are compared. Delaunay mesh generation is used to create random points inside and on the border, which data can be incorporated in these locations. 49 MERRA weather stations as used as data sources to provide the temperature at a specific day and hour. The contours of interpolated temperatures provided in the result section assert RBF is a more accurate method than the Gravity model by showing a smoother and broader range of interpolated data.