Photonic Crystal Fibres: Modelling and Sensitivity Analysis
Abstract
The economic viability of industrial automation hinges on managing the uncertainties inherent in photonic crystal fibres. Model parameters are calibrated against field data and independently validated using deep learning. The analysis identified 6 dominant factors that together explain most of the observed variation. Policymakers may draw on these results when prioritising infrastructure investment.
Keywords:
photonic crystal fibresdeep learningadsorptionair qualitylife cycle assessment
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