1 publication

• Published Subscription Review Article 23 Sep 2026

  Machine Learning Based Optimization of Optical Fiber Parameters for Minimizing Dispersion and Attenuation

  By Sandesh Kulkarni, Yashraj Lade, Sarvesh Mahimkar, Anuj Mane, Vaibhav Godase

  Abstract: Optical fibers provide high-bandwidth and low-loss transmission for modern communication networks; however, attenuation and chromatic dispersion remain two important physical limitations affecting transmission distance, pulse integrity, and system capacity. Conventional optical-fiber design generally relies on analytical calculations and repeated numerical simulations to determine suitable geometric and material parameters. Such approaches become computationally demanding when several fiber parameters are simultaneously optimized. This paper presents a machine-learning-based methodology for predicting and optimizing …

  Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 · pp. 18–28 Read article →