TY - JOUR
T1 - Forecasting the unit cost of a DRAM product using a layered partial-consensus fuzzy collaborative forecasting approach
AU - Chen, Tin Chih Toly
AU - Wu, Hsin Chieh
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/10
Y1 - 2020/10
N2 - 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%.
AB - 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%.
KW - Dynamic random access memory
KW - Fuzzy collaborative forecasting
KW - Layered partial consensus
UR - http://www.scopus.com/inward/record.url?scp=85092926256&partnerID=8YFLogxK
U2 - 10.1007/s40747-020-00146-3
DO - 10.1007/s40747-020-00146-3
M3 - Article
SN - 2199-4536
VL - 6
SP - 479
EP - 492
JO - Complex and Intelligent Systems
JF - Complex and Intelligent Systems
IS - 3
ER -