Parallel method of production rules extraction based on computational intelligence

Abstract

The problem of production rules extraction has been solved based on parallel computing and computational intelligence. The research object is the process of production rules extraction. The purpose of the work is the creation of the production rules extraction method, based on a parallel principle of the construction of the intelligent models, which bring together given data samples in the form of the models based on the decision trees, association rules and negative selection. The developed method allow to significantly reduce the time required for the models synthesis when solving the complex practical problems, characterized by a large amount of the diagnostic data; and the problems, where there is a need to modify the existing diagnostic and recognition models due to the appearance of new information, which is the result of the permanent observation after the state of the research objects and processes. At the same time, the capability of the synthesis of the models that have the high approximating and generalizing abilities is provided.