An interval fuzzy number-based fuzzy collaborative forecasting approach for DRAM yield forecasting

Tin-Chih Chen, Min-Chi Chiu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Most existing fuzzy collaborative forecasting (FCF) methods adopt type-1 fuzzy numbers to represent fuzzy forecasts. FCF methods based on interval-valued fuzzy numbers (IFNs) are not widely used. However, the inner and outer sections of an IFN-based fuzzy forecast provide meaning information that serves different managerial purposes, which is a desirable feature for a FCF method. This study proposed an IFN-based FCF approach. Unlike existing IFN-based fuzzy association rules or fuzzy inference systems, the IFN-based FCF approach ensures that all actual values fall within the corresponding fuzzy forecasts. In addition, the IFN-based FCF approach optimizes the forecasting precision and accuracy with the outer and inner sections of the aggregation result, respectively. Based on the experimental results, the proposed FCF-II approach surpassed existing methods in forecasting the yield of a dynamic random access memory product.

Original languageEnglish
Number of pages12
JournalComplex & intelligent systems
DOIs
StateE-pub ahead of print - 1 Aug 2020

Keywords

  • Fuzzy collaborative forecasting
  • Interval fuzzy number
  • Mixed binary nonlinear programming
  • COLONY OPTIMIZATION ALGORITHM
  • INTELLIGENCE APPROACH
  • INFERENCE SYSTEM
  • UNIT COST
  • TIME
  • PERFORMANCE
  • MODEL

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