ASSOCIATIVE SYSTEM TO PREDICT STRUCTURES IN THE IONOSPHERE

Abstract

Communications are the most important part of our daily life. The ionosphere play an important role in communications due to the conditions of the ionosphere can affect severely the transmitting and receiving information. Therefore, we propose an intelligent system that can predict accurately structures in the ionosphere. We use a morphological associative model. The obtained results of effectiveness from the Leave One out, Hold Out and Ten-Fold Cross validation test were: 89.45%, 97.77% and 95.83%, respectively, when we use only the max memory because min memory showed a bad performance.