Classifying U.S. Manufacturing Plant Locations Using An Artificial Neural Network
Abstract
This paper examines the application of an artificial neural network (ANN) for classifying the contiguous states in the USA according to their manufacturing climate. The application uses a self-organizing paradigm, the ART2. The performance of the ANN was very encouraging. Its results were compared to those obtained from a scoring model that ranked the states utilizing the same criteria. Future work is intended to further improve the network's performance and develop an Artificial Neural System (ANS) that will assist decision makers in selecting the best locations for manufacturing facilities in the U.S.A. The ANS is seen as a key component of an intelligent decision support system for improving and enhancing plant location decision making. © 1992.
Recommended Citation
M. Tarek Gaber and C. O. Benjamin, "Classifying U.S. Manufacturing Plant Locations Using An Artificial Neural Network," Computers and Industrial Engineering, vol. 23, no. 1 thru 4, pp. 101 - 104, Elsevier, Jan 1992.
The definitive version is available at https://doi.org/10.1016/0360-8352(92)90073-S
Department(s)
Engineering Management and Systems Engineering
International Standard Serial Number (ISSN)
0360-8352
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Elsevier, All rights reserved.
Publication Date
01 Jan 1992
