Journal article
Prediction of polymer optical fiber properties using artificial neural networks
- Abstract:
-
Polymer fibers are finding increasing applications in commercial optical communication systems. Polymer optical fibers, with specified desirable consumer characteristics, can be computationally designed. Through the use of an extensive structure - property correlation database, properties of polymers can be predicted by a Neural Network. In this paper we are focusing on glass transition temperature (Tg) that influences a desired outcome in polymeric optical fibers. Performance of such fibers ...
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- Publisher copy:
- 10.1109/CIMSA.2007.4362530
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Authors
Bibliographic Details
- Journal:
- Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA
- Pages:
- 14-18
- Publication date:
- 2007-01-01
- DOI:
- URN:
-
uuid:58153fa7-6f6e-452d-abf9-fa353b8c5035
- Source identifiers:
-
331929
- Local pid:
- pubs:331929
Item Description
- Language:
- English
- Keywords:
Terms of use
- Copyright date:
- 2007
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