title:
 
Soft computing-based decision support tools for spatial data
publication:
 
IJCIS
volume-issue:   6 - sup1
pages:   18 - 33
ISSN:
  1875-6883
DOI:
  doi:10.2991/10.1080/18756891.2013.818185 (how to use a DOI)
author(s):
 
Serge Guillaume, Brigitte Charnomordic, Bruno Tisseyre, James Taylor
publication date:
 
2013
keywords:
 
Fuzzy, zone, learning, geostatistics, FisPro, GeoFIS, agronomy, environment
abstract:
 
In many fields, due to the increasing number of automatic sensors and devices, there is an emerging need to integrate georeferenced and temporal data into decision support tools. Geographic Information Systems (GIS) and Geostatistics lack some functionalities for modelling and reasoning using georeferenced data. Soft computing techniques and software suited to these needs may be useful to implement new functionalities and use them for modelling and decision making. This work presents an open source framework designed for that purpose. It is based upon open source toolboxes, and its design is inspired by the fuzzy software capabilities developed in for ordinary non-georeferenced data. Two real world applications in Agronomy are included, and some perspectives are given to meet the challenge of using soft computing for georeferenced data.
copyright:
 
© The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
full text: