[1] [1] KULKARNI P, TZANAKAKI A, MACHUKA C M, et al. Benefits of Q-factor based Routing in WDM Metro Networks[C]// Proceedings of European Conference on Optical Communication (ECOC 2005), Septem-

          ber 25-29, 2005, Glasgow, UK. London: IET, 2005: 1-2.

[2] [2] RAMAMURTHY B, DATTA D, FENG H, et al. Impact of transmission impairments on the teletraffic performance of wavelength-routed optical networks[J]. Journal of Lightwave Technology, 1999, 17(10): 1713-1723.

[3] [3] PACHNICKE S, PASCHENDA T, KRUMMRICH P M. Physical Impairment Based Regenerator Placement and Routing in Translucent Optical Networks[C]// Proceedings of Optical Fiber Communication Conference (OFC 2008), February 24-28, 2008, San Diego, USA. Pisca-

          taway: IEEE, 2008: 1-3.

[4] [4] MARKIDIS G, SYGLETOS S, TZANAKAKI A, et al. Impairment-

          Constraint-Based Routing in Ultralong-Haul Optical Networks With 2R Regeneration[J]. IEEE Photonics Technology Letters, 2007, 19(6): 420-422.

[5] [5] tically Calculated Q-Factor[C]// Proceedings of Optical Fiber Communi-

          cation Conference (OFC 2006), March 5-10, 2006, Anaheim, USA. Piscataway: IEEE, 2006: 1-3.

          POLITI C T, ANAGNOSTOPOULOS V, MATRAKIDIS C, et al. Physical Layer Impairment Aware Routing Algorithms Based on Analy-

[6] [6] BARLETTA L, GIUSTI A, ROTTONDI C, et al. QoT Estimation for Unestablished Lighpaths using Machine Learning[C]// Proceedings of Optical Fiber Communication Conference (OFC 2017), March 19-23, 2017, Los Angeles, USA. Piscataway: IEEE, 2017: 1-3.

[7] [7] LEIBRICH J, ROSENKRANZ W. Efficient numerical simulation of multichannel WDM transmission systems limited by XPM[J]. IEEE Photonics Technology Letters, 2003, 15(3): 395-397.

[8] [8] TAO Z, YAN W, LIU L, et al. Simple Fiber Model for Determination of XPM Effects[J]. Journal of Lightwave Technology, 2011, 29(7): 974-986.

[9] [9] SHAO J, LIANG X, KUMAR S. Comparison of Split-Step Fourier Schemes for Simulating Fiber Optic Communication Systems[J]. IEEE Photonics Journal, 2014, 6(4): 1-16.

[10] [10] POGGIOLINI P, BOSCO G, CARENA A, et al. The GN-Model of Fiber Non-Linear Propagation and its Applications[J]. Journal of Lightwave Technology, 2014, 32(4): 694-721.

[11] [11] dings of Optical Fiber Communication Conference (OFC 2018), March 11-15, 2018, San Diego, USA. Piscataway: IEEE, 2018: 1-3.

          MO W, HUANG Y, ZHANG S, et al. ANN-Based Transfer Learning for QoT Prediction in Real-Time Mixed Line-Rate Systems[C]//Procee-

[13] [13] MORAIS R M, PEDRO J. Evaluating Machine Learning Models for QoT Estimation[C]//Proceedings of International Conference on Transp-

          arent Optical Networks (ICTON 2018), July 1-5, 2018, Bucharest, Roman-

          ia. Piscataway: IEEE, 2018: 1-4.

[14] [14] BOUDA M, ODA S, AKIYAMA Y, et al. Demonstration of Contin-

          uous Improvement in Open Optical Network Design by QoT Prediction using Machine Learning[C]//Proceedings of Optical Fiber Communication Conference(OFC 2019), March 3-7, 2019, San Diego, USA. Piscataway: IEEE, 2019: 1-3.

[15] [15] PANAYIOTOU T, SAVVA G, SHARIATI B, et al. Machine Learning for QoT Estimation of Unseen Optical Network States[C]//Proceedings of Optical Fiber Communication Conference(OFC 2019), March 3-7, 2019, San Diego, USA. Piscataway: IEEE, 2019: 1-3.

[16] [16] AZZIMONTI D, ROTTONDI C, TORNATORE M. Using Active Learning to Decrease Probes for QoT Estimation in Optical Networks

          [C]//Proceedings of Optical Fiber Communication Conference(OFC 2019), March 3-7, 2019, San Diego, USA. Piscataway: IEEE, 2019: 1-3.

[17] [17] ALADIN S, TREMBLAY C. Cognitive Tool for Estimating the QoT of New Lightpaths[C]// Proceedings of Optical Fiber Communication Conference(OFC 2018), March 11-15, 2018, San Diego, USA. Piscataway: IEEE, 2018: 1-3.