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000910115 037__ $$aFZJ-2022-03623
000910115 1001_ $$0P:(DE-Juel1)195622$$aRobledo, Jose Ignacio$$b0$$ufzj
000910115 1112_ $$aJCNS WORKSHOP 2022 TRENDS AND PERSPECTIVES IN NEUTRON SCATTERING: EXPERIMENTS AND DATA ANALYSIS IN THE DIGITAL AGE$$cEvangelische Akademie Tutzing$$d2022-10-11 - 2022-10-14$$wGermany
000910115 245__ $$aVirtual Experiments combined with Machine Learning to improve Data Evaluation of SANS measurements
000910115 260__ $$c2022
000910115 3367_ $$033$$2EndNote$$aConference Paper
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000910115 520__ $$aIn this work we present our research line that has begun as part of the “Global Neutron Scientist” (GneuS) call N.º 1 this year. We present our strategy to combine virtual experiments with Machine Learning (ML) techniques to improve the data evaluation procedure in Small Angle Neutron Scattering (SANS) experiments. In particular, we describe the virtual experiments we are planning to do at a SANS instrument at MLZ with the VITESS software [1] to create a training database for ML algorithms, and we discuss aproposed first step exploratory analysis to the generated data using Multivariate Statistical methodologies. This analysis will give insight to the adequate ML algorithms that we will explore. [1] C. Zendler, K. Lieutenant, D. Nekrassov, M. Fromme, Vitess 3 – Virtual Instrumentation Tool for the European Spallation, J. Phys. Conf. Ser. 528 (2014) 012036.
000910115 536__ $$0G:(DE-HGF)POF4-632$$a632 - Materials – Quantum, Complex and Functional Materials (POF4-632)$$cPOF4-632$$fPOF IV$$x0
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000910115 7001_ $$0P:(DE-Juel1)178839$$aLieutenant, Klaus$$b1$$ufzj
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