A new GRASS GIS fuzzy inference system for massive data analysis
GIS systems are frequently coupled with fuzzy logic systems implemented in statistical packages. For large GIS data sets including millions or tens of millions of cells, such an approach is relatively time-consuming. For very large data sets there is also an input/output bottleneck between the GIS and external software. The aim of this paper is to present low-level implementation of Mamdanis fuzzy inference system designed to work with massive GIS data sets, using the GRASS GIS raster data processing engine.
grass gis inference system data analysis fuzzy logic