Prediction of polymer optical fiber properties using artificial neural networks - ORA - Oxford University Research Archive

Back to Search

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 ...
Expand abstract
Collapse abstract

Actions

Email

Email this record

Send the bibliographic details of this record to your email address.

Your Email
Please enter the email address that the record information will be sent to.

-
Your message (optional)
Please add any additional information to be included within the email.
Cite

Cite this record

APA Style

Xi, C., Sztandera, L., & Cartwright, H. (2007). Prediction of polymer optical fiber properties using artificial neural networks. Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA, 14–18.

MLA Style

Xi, C., et al. “Prediction of Polymer Optical Fiber Properties Using Artificial Neural Networks.” Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA, 2007, pp. 14–18.

Chicago Style

Xi, C, L Sztandera, and H Cartwright. 2007. “Prediction of Polymer Optical Fiber Properties Using Artificial Neural Networks.” Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA, 14–18.
Tweet
Print

Access Document

Publisher copy:: 10.1109/CIMSA.2007.4362530

Authors

+ Xi, C More by this author

Role:

Author

+ Sztandera, L More by this author

Role:

Author

+ Cartwright, H More by this author

Role:

Author

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:: 10.1109/CIMSA.2007.4362530

Item Description

Language:: English
Keywords:: QSPR

Glass transition temperature

Neural network
Pubs id:: pubs:331929
UUID:: uuid:58153fa7-6f6e-452d-abf9-fa353b8c5035
Local pid:: pubs:331929
Source identifiers:: 331929
Deposit date:: 2013-02-20

Terms of use

Copyright date:: 2007

Licence:: Terms and Conditions of Use for Oxford University Research Archive

Metrics

Views and Downloads

About views and downloads

If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP