Artificial intelligence designer for optical Fibers: Inverse design of
The inverse design model (IDM) aims to provide the inverse design of the structural parameters according to the optical characteristics. The optimal FPM can be obtained using a
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Inverse Optimization Algorithm Fiber
A Large-Scale Sensor Layout Optimization Algorithm for Improving the
The inverse finite element method (iFEM) based on fiber grating sensors has been demonstrated as a shape sensing method for health monitoring of large and complex engineering
Inverse design of broadband and dispersion-flattened highly GeO
Reverse design of highly GeO 2 -doped silica optical fibers with broadband and flat dispersion profiles is proposed using a neural network (NN) combined with a particle swarm
Inverse design of few-mode fiber by Neural Network for weak-coupling
We use a neural network to inversely design a four-ring few-mode fiber for weak-coupling optimization so as to support MIMO-less MDM optical communication. This method provides high-accuracy, high
Inverse design of mode-locked fiber laser by particle swarm
In the next section we demonstrate how to utilise Particle Swarm Optimization algorithm to implement mapping between the desired pulse characteristics and the laser system design
(PDF) Artificial Intelligence Designer for Optical Fibers: Inverse
In this work, artificial intelligence (AI) is trained to “study” optical fibers as an AI optical fiber scientist. The dataset is constructed on the structural parameters and confinement...
Data-driven inverse design of mode-locked fiber lasers
Here, a completely data-driven approach for the inverse design of MLFLs is proposed, which significantly reduces the computational complexity and achieves a fast automatic inverse design of...
Artificial Intelligence and Machine Learning in Optical Fiber Sensors
In recent years, AI techniques have been increasingly integrated with OFS systems for system-level optimization. In this paper, we classify the applications of AI in OFS into two distinct categories based
AI-Assisted Inverse Design Methods of Few-Mode Multi-Core Fiber
We propose two machine learning-based inverse design methods for few-mode multi-core fiber, utilizing neural networks and particle swarm optimization algorithms to achieve high