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

机译:使用遗传编程预测短期和长期价格预测的宠物芯片价格的解决方案

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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 [13]. 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 [13]. 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 the research question considerably.
机译:如今,对经济环境发生的情况预测对管理人员在适当的物品上进行正确投资的至关重要的作用。我们表明,在宠物市场中,神经模糊的混合模型如何协助管理人员决策[13]。在这项研究中,目标是通过另一个智能工具预测相同的项目,该工具致力于携带进化处理机制。同样,这里预测的物品是PET(聚乙烯对苯二甲酸乙二醇酯),它是纺织工业的原料,对油价波动非常敏感,以及其他一些因素,如需求和供应比例。主要思想正在通过M.S.提出的AHIS模型来源。 Fazli和J.f.Lebraty在2013年[13]。在这种通信中,混合模块被遗传编程代替。最后,已经进行了模拟,并将其与三种不同模型答案进行了比较,以前呈现。结果表明,支持模糊系统和神经网络的基因编程结果(表现如混合模型)大大满足了研究问题。

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