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

摘要

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.