Grey system theory and fuzzy time series forecasting for the growth of green electronic materials

Abstract

The development of green materials is an important part of corporate social responsibility. Companies need to use resources legitimately and have environmental protection responsibility. Forecasting the growth trend of green copper clad laminate (CCL) material is crucial for manufacturers of printed circuit boards and green CCLs. Early and accurate understanding of such trends in this industry can lead to the early acquisition of opportunities for related markets and technological development. Because historical data samples associated with green CCL are small and typically lack a normal distribution, employing conventional regression analysis or time series models for forecasting is not suitable for testing-related presumptions. To address this issue, this study adopts grey system theory (GST) and a fuzzy time series (FTS) model as forecasting methods. The results show that effective forecasting can be achieved by applying either a GM (1,1) α model or heuristic FTS model to the data of a small and non-normally distributed sample.

Keywords:

• forecasting
• heuristic fuzzy time series
• grey system theory (GST)
• green electronic material
• production research
• corporate social responsibility