Volume 6, Issue sup1, January 1970, Pages 18 - 33
Soft computing-based decision support tools for spatial data
- Serge Guillaume, Brigitte Charnomordic, Bruno Tisseyre, James Taylor
- Corresponding Author
- Serge Guillaume
Available Online 9 January 2017.
- https://doi.org/10.1080/18756891.2013.818185How to use a DOI?
- Fuzzy, zone, learning, geostatistics, FisPro, GeoFIS, agronomy, environment
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Serge Guillaume AU - Brigitte Charnomordic AU - Bruno Tisseyre AU - James Taylor PY - 2017 DA - 2017/01 TI - Soft computing-based decision support tools for spatial data JO - International Journal of Computational Intelligence Systems SP - 18 EP - 33 VL - 6 IS - sup1 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2013.818185 DO - https://doi.org/10.1080/18756891.2013.818185 ID - Guillaume2017 ER -