Semiconductor Yield Forecasting Using Quadratic-Programming-Based Fuzzy Collaborative Intelligence Approach
Joint Authors
Toly Chen, Tin-Chih
Wang, Yu-Cheng
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-30
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Several recent studies have proposed fuzzy collaborative forecasting methods for semiconductor yield forecasting.
These methods establish nonlinear programming (NLP) models to consider the opinions of experts and generate fuzzy yield forecasts.
Such a practice cannot distinguish between the different expert opinions and can not easily find the global optimal solution.
In order to solve some problems and to improve the performance of semiconductor yield forecasting, this study proposes a quadratic-programming- (QP-) based fuzzy collaborative intelligence approach.
American Psychological Association (APA)
Toly Chen, Tin-Chih& Wang, Yu-Cheng. 2013. Semiconductor Yield Forecasting Using Quadratic-Programming-Based Fuzzy Collaborative Intelligence Approach. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1010286
Modern Language Association (MLA)
Toly Chen, Tin-Chih& Wang, Yu-Cheng. Semiconductor Yield Forecasting Using Quadratic-Programming-Based Fuzzy Collaborative Intelligence Approach. Mathematical Problems in Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1010286
American Medical Association (AMA)
Toly Chen, Tin-Chih& Wang, Yu-Cheng. Semiconductor Yield Forecasting Using Quadratic-Programming-Based Fuzzy Collaborative Intelligence Approach. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1010286
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1010286