Logical aggregation for modular neural networks in currency exchange rate forecasting

Abstract

In this paper fields of research are modular neural networks and consistent real-valued logic as a technique for aggregation of the modules. Aggregation is done using logical and pseudo-logical aggregation based on interpolative Boolean algebra (IBA). IBA is technically realized through generalized Boolean polynomials. The proposed technique expands the existing base of modular neural network models and shows respectable results in forecasting currency exchange rates