Representation and classification of geospatial data: a comparison of kohonen's maps and the Neural Gas Method

Ingeniería e Investigación

关键词: Gepgraphic information System (GIS);    spatial data mining;    neuronal networks;    Self organizating map (SOM);    kohonen;    neural gas;   

DOI  :  

来源: DOAJ

【 摘 要 】

Approximately 80% of all existing information in the world correspond to geo-referenced information. This creates an increasing necessity to have tools more flexible, precise and easy to use to the visualization, exploration and classification of great volumes of geospatial data. Additionally its necessary achieve smaller times to process this kind of information. In this preliminary investigation, different techniques are compared to visualize and to classify geo-referenced data using two types of neuronal networks: Kohonen's maps (SOM) and the Neural Gas Method (NG). For the visualizaton cases, SOM showed a better performance than NG, ocurring the opposite case for the classification examples.

【 授权许可】

Unknown