A Framework for integration between Artificial Neural Network & Geographical Information System, Slum prediction as the case study

Geographical information system (GIS) is a powerful tool in managing and presenting spatial referenced data science it has a lot of geographic functions such as data integration, mapping, overlaying, buffering, projection....etc, but on the contrary it is a limited tool in decision aiding of spatial decision problems. It can't stand alone in taking decision in spatial problem environment. In the same time, decision support system (DSS) is an important aiding tool which supports decision makers to get the best selection among several alternatives and preferences. But also it can’t stand alone in making a decision containing spatial dimension because it’s shortage in managing and treating spatial data. So the need for modern GIS is become essential to extend the functionality of GIS to merge the strength of both GIS and DSS to get a powerful spatial decision support system (SDSS). To achieve this purpose a lot of integration can be done between GIS and artificial neural networks (ANN), fuzzy logic (FL), genetic algorithms (GA), expert systems (ES) and many more. One of the most important integration is the integration between ANN and GIS. By this way GIS will become more intelligent as including modeling and simulation capabilities. This coupling can be used for many applications for the purposes of improved decision-making. This paper suggests a framework for this integration which can be used later as a standard framework.