Trade Surplus Analysis Using Self-Organizing Data Mining Based on GMDH Principle

A approach is suggested for designing and developing a trade surplus influence factors correlation analysis application where GMDH principle is used for generating it more easily. This approach uses self-organizing data mining importing the concept of evolution based on principle of GMDH and enables the knowledge extraction process on a highly automated level and generates optimal complex model in an objective way. In correlation analysis of trade surplus in imports and exports, considering domestic economic factors modelpsilas structure is created automatically using self-organizing data mining technology and the internal correlations between these factors are found.