AI Modeling involves creating algorithms and frameworks that enable artificial intelligence systems to learn from data and make predictions or decisions based on that learning. It is crucial in various applications, including natural language processing, image recognition, and recommendation systems. The effectiveness of an AI model heavily relies on the quality and quantity of the data used for training, as well as the algorithms and techniques applied.

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Machine Learning Model for EDFA Predicting SHB Effects

Experiments show that machine learning model of an EDFA is capable of modelling spectral hole burning effects accurately. As a result, it significantly outperforms black-box models that neglect inhomogeneous effects. Model achieves a record average RMSE of 0.0165 dB between the model predictions and measurements.