Solar Storm Type Classification Using Probabilistic Neural Network Compared with the Self-organizing Map

One of the task of the LAPAN is making obsevation and forecasting of solar storms disturbance. This disturbances can affect the earth's electromagnetic field that disrupt the electronic and navigational equipment on earth. It would be dangerous to human life if not properly anticipated. LAPAN wanted a computer application that can automatically classify the type of solar storms, which became part of early warning systems to be created. Therefore we from Petra Christian University Informatics Engineering Department and the Indonesian National Aeronautics and Space Agency conduct joint research on the classification of solar storms. The classification of the digital images of solar storm / sunspot groups is based on “Modified Zurich Sunspot Classification System” which is widely used. Classification method that we use here is the Probabilistic Neural Networks. The result of testing is promising because it has an accuracy of 94% for testing data. The accuracy is better than the accuracy of similar applications we've built with a combination of methods Self-Organizing Map and KNearest Neighbor.