Study and Analysis of Data Analysis Systems (Reconstruction of a Learning Data from the Initial Data)

Abstract

Data analysis methods have been widely used in various domains, such as medical, marketing, and agriculture. Since they have a good performance to reduce massive data. Unfortunately, those methods are limited without the usage of Computer Technologies (computer technologies, 'CT'), which lead to developing autonomous systems capable of making appropriate decisions in each situation, by the realization of algorithm and artificial intelligence (artificial intelligence, 'AI') tools. This paper presents the coupling of principal component analysis (principal component analysis, 'PCA') mathematical method and the counter propagation artificial neural network (counter propagation network, 'CPN'), as an objective to reduce and minimize the data before starting learning, improve the learning process results and accuracy of the classification and eliminate the obstacles detected between inputs objects. The results of this combination have been compared with the results of the standard CPN.