The Development of Self-Organization Techniques in Modelling: A Review of the Group Method of Data Handling (GMDH)

The necessity of modelling is well established since the structural identification of a process is essential in analysis, control and prediction. In the past, limited information on system behaviour has driven researchers to introduce modelling techniques with a broad range of assumptions on systems' characteristics. Statistical modelling methods, which are based on these assumptions have generally failed to fully capture the dynamic characteristics of the process. The development of neural networks have partly improved the the modelling procedure but their high degree of subjectiveness in the definition of some of their parameters as well as the demand of long data data samples remain significant obstacles. On the other hand, real world systems like financial markets have a high degree of volatility and the utilisation of long data samples tends to remove and in effect, filter the dynamic characteristics of the process.........