A Methodology for Automatic Analysis and Modeling of Spatial Environmental Data

摘要

The research paper deals with a step-by-step methodology for the automatic modeling of geospatial environmental data. The methodology proposed is based on general regression neural networks (GRNN) and probabilistic neural networks (PNN) as modeling tools. GRNN and PNN are nonparametric nonlinear models suitable for the automatic analysis, modeling, and spatial predictions of complex environmental data. The simulated and real data case studies illustrating the methodology are considered and discussed.