Forecasting the unit cost of a DRAM product using a layered partial-consensus fuzzy collaborative forecasting approach

Tin Chih Toly Chen, Hsin Chieh Wu*

*此作品的通信作者

研究成果: Article同行評審

11 引文 斯高帕斯(Scopus)

摘要

A layered partial-consensus fuzzy collaborative forecasting approach is proposed in this study to forecast the unit cost of a dynamic random access memory (DRAM) product. In the layered partial-consensus fuzzy collaborative forecasting approach, the partial-consensus fuzzy intersection (PCFI) operator is applied instead of the prevalent fuzzy intersection (FI) operator to aggregate the fuzzy forecasts by experts. In this way, some meaningful information, such as the suitable number of experts, can be obtained through observing changes in the PCFI result when the number of experts varies. After applying the layered partial-consensus fuzzy collaborative forecasting approach to a real case, the experimental results revealed that the layered partial-consensus fuzzy collaborative forecasting approach outperformed three existing methods. The most significant advantage was up to 13%.

原文English
頁(從 - 到)479-492
頁數14
期刊Complex and Intelligent Systems
6
發行號3
DOIs
出版狀態Published - 10月 2020

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