<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gournellos, Th.</style></author><author><style face="normal" font="default" size="100%">Evelpidou, N.</style></author><author><style face="normal" font="default" size="100%">Vassilopoulos, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An example of join of GIS with artificial intelligence methods (fuzzy logic and neural networks): Application to geomorphology.</style></title><secondary-title><style face="normal" font="default" size="100%">10th International Congress</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><publisher><style face="normal" font="default" size="100%">Bulletin of the Geological Society of Greece</style></publisher><volume><style face="normal" font="default" size="100%">XXXVI</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper we are studying the erosional procedures on the basis of Geographical Information&lt;br&gt;Systems (GIS) and Artificial Intelligence (AI) methods. More precisely we use fuzzy logic rules to&lt;br&gt;estimate the erosion risk index for the surface rocks and a model of neural networks to spatially categorise&lt;br&gt;the erosion risk index. The described procedure is applied at Zakynthos island, where a&lt;br&gt;complete spatial database already exists.&lt;/p&gt;</style></abstract></record></records></xml>