Self-organizing learning array and its application to economic and financial problems

A new Self-Organizing Learning Array (SOLAR) system has been realized in software. SOLAR is capable of handling a wide variety of classification problems. It has a regular array structure with sparsely interconnected computing elements and local learning rules. Unlike artificial neural networks, this structure scales well to large systems capable of solving complex pattern recognition and classification tasks. This paper shows its application in economic and financial fields. Several prediction and classification cases are studied. The results have been compared with the existing methods.