| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 507191 | Computers & Geosciences | 2011 | 7 Pages |
Abstract
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 Mamdani’s fuzzy inference system designed to work with massive GIS data sets, using the GRASS GIS raster data processing engine.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
JarosŁaw Jasiewicz,