Abstract
In the manufacturing process of yarns for the textile industry, often encountered is the problem of how to select a substitute (from the warehouse) for a brand of cotton in the cotton allocation that is currently in use but running out of the raw material. A model that uses fuzzy dynamic integrated judgment (FDIJ) provides a very useful tool in solving this problem. In view of several factors in cotton allocations, the FDIJ is made for cotton selection according to the data feedback from previous production runs. The main objective of this paper is to explain how the data feedback can be stored in a fuzzy dynamic relationship dictionary which generates a fuzzy dynamic relation to be used in the learning ability in the problem of cotton allocation.
| Original language | English |
|---|---|
| Pages (from-to) | 277-290 |
| Number of pages | 14 |
| Journal | Information Sciences |
| Volume | 94 |
| Issue number | 1-4 |
| State | Published - Oct 1996 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Science Applications
- Information Systems
- Information Systems and Management
- Statistics, Probability and Uncertainty
- Electrical and Electronic Engineering
- Statistics and Probability
Cite this
An application of fuzzy dynamic integrated judgment to cotton allocation. / Zhao, Lin; Peng, Chang Shyh; Cheng, Shih-Chuan.
In: Information Sciences, Vol. 94, No. 1-4, 10.1996, p. 277-290.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An application of fuzzy dynamic integrated judgment to cotton allocation
AU - Zhao, Lin
AU - Peng, Chang Shyh
AU - Cheng, Shih-Chuan
PY - 1996/10
Y1 - 1996/10
N2 - In the manufacturing process of yarns for the textile industry, often encountered is the problem of how to select a substitute (from the warehouse) for a brand of cotton in the cotton allocation that is currently in use but running out of the raw material. A model that uses fuzzy dynamic integrated judgment (FDIJ) provides a very useful tool in solving this problem. In view of several factors in cotton allocations, the FDIJ is made for cotton selection according to the data feedback from previous production runs. The main objective of this paper is to explain how the data feedback can be stored in a fuzzy dynamic relationship dictionary which generates a fuzzy dynamic relation to be used in the learning ability in the problem of cotton allocation.
AB - In the manufacturing process of yarns for the textile industry, often encountered is the problem of how to select a substitute (from the warehouse) for a brand of cotton in the cotton allocation that is currently in use but running out of the raw material. A model that uses fuzzy dynamic integrated judgment (FDIJ) provides a very useful tool in solving this problem. In view of several factors in cotton allocations, the FDIJ is made for cotton selection according to the data feedback from previous production runs. The main objective of this paper is to explain how the data feedback can be stored in a fuzzy dynamic relationship dictionary which generates a fuzzy dynamic relation to be used in the learning ability in the problem of cotton allocation.
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UR - http://www.scopus.com/inward/citedby.url?scp=0030266247&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:0030266247
VL - 94
SP - 277
EP - 290
JO - Information Sciences
JF - Information Sciences
SN - 0020-0255
IS - 1-4
ER -