Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

Using Fuzzy Regression and Neural Network to Predict Organizational Performance

Authors
Liang-Hung Lin 0
Corresponding Author
Liang-Hung Lin
0National Kaohsiung University of Applied Sciences
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.137How to use a DOI?
Keywords
multiple regression analysis ; fuzzy regression ; neural network
Abstract
As everyone knows, multiple regression analysis is an important approach to prediction studies. However, regression model has some limitations and constraints in the real world practices. This study applied fuzzy regression using neural network (FRNN) to predict organizational performance, and the findings indicate that the accuracy rate analysis supported FRNN to be a better method to predict nonlinear variables.
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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.137How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Liang-Hung Lin
PY  - 2006/10
DA  - 2006/10
TI  - Using Fuzzy Regression and Neural Network to Predict Organizational Performance
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.137
DO  - https://doi.org/10.2991/jcis.2006.137
ID  - Lin2006/10
ER  -