Case-Based Reasoning (CBR) to estimate the Q-factor in optical networks: An initial approach

Author

Jiménez, T. ; de Miguel, I. ; Aguado, J.C. ; Durán, R.J. ; Merayo, N. ; Fernández, N. ; Sánchez, D. ; Fernández, P. ; Atallah, N. ; Abril, E.J. ; Lorenzo, R.M.

Author_Institution

Univ. of Valladolid (UVa), Valladolid, Spain

fYear

2011

fDate

20-22 July 2011

Firstpage

181

Lastpage

184

Abstract

We discuss the potential of Case-Based Reasoning (CBR) to estimate the Q-factor in optical networks. CBR is an artificial intelligence technique which solves new problems based on the solutions of similar past problems. In this paper, as a first step, we consider a very simple scenario and develop a CBR method to estimate the Q-factor in optical links with cascades of amplifiers. While this is a toy problem, the results obtained are promising, as the CBR system performs a successful classification into good quality or low quality of transmission links in 94% of cases.

Keywords

Q-factor; amplifiers; case-based reasoning; optical links; Q-factor; amplifiers; artificial intelligence; case-based reasoning; optical links; optical networks; Analytical models; Cognition; Databases; Knowledge based systems; Optical fiber amplifiers; Optical fiber networks; Q factor;

fLanguage

English

Publisher

ieee

Conference_Titel

Networks and Optical Communications (NOC), 2011 16th European Conference on

Conference_Location

Newcastle-Upon-Tyne

Print_ISBN

978-1-61284-753-5

Electronic_ISBN

978-1-86135-373-3

Type

conf

Filename

5996263