GVNNWR: Geographically and Vertically Neural Network Weighted Regression for Three-dimensional Spatial Non-stationarity Modeling

This repository provides complete experimental implementation methods and evaluation result generation for the Geographically and Vertically Neural Network Weighted Regression, which develops a 3D Spatial Proximity Neural Network (SPNN3D) that integrates multi-dimensional distance metrics within a neural framework to model nonlinear spatial proximity and finally be combined with GNNWR to better characterize complex spatial non-stationarity in three-dimensional geographical space. This contains the code of model implementation and model evaluation, as well as simulation datasets and real case datasets.