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 Lin1
1National Kaohsiung University of Applied Sciences
Corresponding Author
Liang-Hung Lin
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.

Copyright
© 2006, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
Series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
10.2991/jcis.2006.137
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.137How to use a DOI?
Copyright
© 2006, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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  - Proceedings of the 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  -