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5 citations found for Archibald, R.
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It is demonstrated how k nearest neighbor machine learning methods can be used to classify small-angle scattering data for the most appropriate model to use for data analysis. The results show the promise of machine learning for helping small-angle scattering practitioners translate measured data into scientific results.
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It is shown that artificial neural networks can be used to predict the location and shape of neutron Bragg peaks, resulting in increased integration accuracy.
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It is demonstrated that using three-dimensional profile fitting of Bragg peaks increases the accuracy and resolution of neutron crystallographic data collected from proteins and reveals new features in nuclear density maps calculated from these data.