IMPROVING BUSINESS RULES MANAGEMENT THROUGH THE APPLICATION OF ADAPTIVE BUSINESS INTELLIGENCE TECHNIQUE

Abstract

Recently, swarm intelligence is becoming a powerful tool for optimizing operations of various businesses. Swarm intelligence is an artificial intelligence technique which study behavior of decentralized, self-organized systems. The goal of the authors of this paper is to elaborate swarm intelligence for business rules management improvement. The paper introduces the decision making model which is based on the application of Artificial Neural Networks (ANNs) and Particel Swarm Optimization (PSO) algorithm. In the proposed decision making model ANNs are applied in order to make the analysis of data and to calculate the decision. The training of ANNs is based on the application of PSO algorithm. The core idea of this algorithm application is to select the "global best" ANN for decision making and to adapt the weights of other ANNs towards the weights of the best network. The potentiality of PSO algorithm application for improving business rules management is shown in the case study.