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Machine learning and Silicon Photonic Sensor for Complex Chemical Components Determination

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Abstract

We propose an integrated microring resonator sensing system based on Backward-Propagation Neural Networks (BPNN)-Adaboost algorithm to predict component fraction in binary liquid mixtures. A minimum absolute error of 0.0023 and mean squared error of 0.000345 is achieved by this training model.

© 2018 The Author(s)

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