A Solution for Forecasting PET Chips Prices for both Short-Term and Long-Term Price Forecasting, Using Genetic Programming

摘要

Nowadays, forecasting on what will happen in economic environments plays a crucial role for managers to invest correctly on appropriate items. We showed that in PET market how a neuro-fuzzy hybrid model can assist the managers in decision-making. In this research, the target is to forecast the same item through another intelligent tool which obeys the evolutionary processing mechanisms. Again, the item for prediction here is PET (Poly Ethylene Terephthalate) which is the raw material for textile industries and it is highly sensitive against oil price fluctuations and also some other factors such as the demand and supply ratio. The main idea is coming through AHIS model which was presented by M.S. Fazli and J.F. Lebraty in 2013. In this communication, the hybrid module is substituted with genetic programming. Finally, the simulation has been conducted and compared to three different models answers which were presented before. The results show that Genetic programming results (acting like hybrid model) which support both Fuzzy Systems and Neural Networks satisfy tile research question considerably.