Automatic generation algorithms of network models for complex systems

Abstract

Presently, lots of theory achievements have been gotten on the modeling of complex systems. However, it is necessary that theory achievements are applied into practice. In addition, it is difficult that models of complex systems are automatically constructed. So, a novel "draw-net" algorithm based on a structure space is presented to realize automatic network model graph generation for complex systems. The structure space is designed with a special data structure, which is used to save the basic information of the network model. Then different spaces are defined to manage the classified information according to certain operating sequence. The generation model is based on classification spaces, and these works contain the computing and the drawing of graphic objects. In the generation process, the iterative calculation is used; the whole model is produced with nodes, relationships, and parameters eventually. Finally, an example on making network models is used to illustrate the proposed algorithm. It shows this algorithm is feasible, and can satisfy realistic requirements. Simultaneously, it is discovered that the auto-generation arithmetic has a good universality, and can be widely extended in the practices.