Evolution Methods of Formation of Neuronet Models of Complex Economic Systems

The article analyses principles of formation of neuronet models of complex economic systems. It justifies prospectiveness of use of artificial intellect methods when modelling complex economic systems. It shows a possibility of use of evolution methods when forming neuronet models of complex economic systems for ensuring invariance of their generalising properties. It offers an algorithm with a genome from operons of fixed length. It considers all operons from the point of view of functional positions. It notes a specific feature of the algorithm, which allows excluding anthropogenic factors when selecting the neuronet models architecture. It proves adequacy of the formed neuronet models of complex economic systems.