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Publikationen im Bereich ML

2023

[19] D. Schirmer, S. Khan, A. Radha Krishnan , “Summary report on machine learning-based applications at the synchrotron light source DELTA”, Proc. of ICALEPCS 2023, Cape Town, South Africa, TUPDP202.

[18] D Schirmer 2023 J. Phys.: Conf. Ser. 2420 012069, “A machine learning approach to electron orbit control at the 1.5 GeV synchrotron light source DELTA”, doi:10.1088/1742-6596/2420/1/012069.

[17] D. Schirmer, A. Althaus, S. Hüser, S. Khan, T. Schüngel, “Machine learning-based optimization of storage ring injection efficiency”, Proc. of IPAC 2023, Venice, Italy, WEPA106.

2022

[16] D. Schirmer, “A Machine learning approach to electron orbit control at the 1.5 GeV synchrotron light source DELTA”, Proc. of IPAC 2022, Bangkok, Thailand, pp. 1137-1140, doi:10.18429/JACoW-IPAC2022-TUPOPT058.

[15] A. Radha Krishnan, B. Büsing, A. Held, H. Kaiser, S. Khan, C. Mai, Z. Usfoor, V. Vijayan, “Investigation of spectro-temporal properties of CHG radiation at DELTA”, Proc. of IPAC 2022, Bangkok, Thailand, pp. 1423-1426, doi:10.18429/JACoW-IPAC2022-TUPOMS012.

[14] D. Schirmer, A. Althaus, T. Schüngel, “Machine learning methods for chromaticity control at the 1.5 GeV synchrotron light source DELTA”, Proc. of IPAC 2022, Bangkok, Thailand, pp. 1141-1144, doi:10.18429/JACoW-IPAC2022-TUPOPT059.

[13] S. Hüser, “Implementierung neuartiger Optimierungsalgorithmen an der Speicherringsanlage DELTA”, Diploma Thesis, TU Dortmund, May 2022.

[12] T. Schüngel, “Development of a Container-Based Work Environment for an automated Optimization of the Sextupole Settings and Injection Efficiency using Machine-Learning at the Storage Ring DELTA”, Master’s Thesis, TU Dortmund, August 2022.

2021

[11] D. Schirmer, “Machine learning applied to automated tunes control at the 1.5 GeV synchrotron light source DELTA”, Proc. of IPAC 2021, Campinas, Brazil, pp. 3379-3382, doi:10.18429/JACoW-IPAC2021-WEPAB303.

[10] D. Schirmer, A. Althaus, S. Hüser, S. Khan, T. Schüngel, “Machine Learning Projects at the 1.5 GeV Synchrotron Light Source DELTA”, Proc. of ICALEPCS 2021, Shanghai, China, pp. 631-635, doi:10.18429/JACoW-ICALEPCS2021-WEPV007.

2020

[9] D. Schirmer, “Machine Learning Applied to Automated Tunes Control at the 1.5 GeV Synchrotron Light Source DELTA”, DELTA Internal Report (2020). 

[8] D. Schirmer, “Machine Learning Applied to Automated Orbit Control at the 1.5 GeV Electron Storage Ring DELTA”, DELTA Internal Report (2020).

2019

[7] D. Schirmer, “Orbit Correction with Machine Learning Techniques at the Synchrotron Light Source  DELTA”, Proc. of ICALEPCS 2019, New York, USA, pp. 1426-1430, doi:10.18429/JACoW-ICALEPCS2019-WEPHA138

[6] D. Schirmer and A. Althaus, “Integration of a Model Server into the Control System of the Synchrotron Light Source DELTA”, Proc. of ICALEPCS 2019, New York, USA, pp. 1421-1425, doi:10.18429/JACoW-ICALEPCS2019-WEPHA137.

2018

[5] D. Schirmer, “Intelligent Controls for the Electron Storage Ring DELTA”, Proc. of IPAC 2018, Vancouver, Canada, pp. 4855-4858, doi:10.18429/JACoW-IPAC2018-THPML085.

2017

[4] D. Schirmer, A. Althaus, P. Hartmann, D. Rohde, “Control System Projects at the Electron Storage Ring DELTA”, Proc. of ICALEPCS 2017, Barcelona, Spain, pp. 1361-1365, doi: 10.18429/JACoW-ICALEPCS2017-THPHA013

2006

[3] D. Schirmer, P. Hartmann, T. Büning, D. Müller, “Electron Transport Line Optimization Using Neural Networks and Genetic Algorithms”, Proc. of EPAC 2006, Edinburgh, Scotland, pp. 1948-1950, WEPCH013.

2005

[2] T. Büning, D. Müller, “Entwurf und Vergleich unterstützender Systeme zur Verbesserung der Injektionseffizienz von DELTA, basierend auf Evolutionsstrategien und neuronalen Netzen”, Diploma Thesis, TU Dortmund, 2005.

2003

[1] E. Zimoch, “Entwicklung und Einsatz eines intelligenten Agentensystems zur Optimierung der Injektion in den Speicherring der Synchrotronstrahlungsquelle DELTA”, dissertation, TU Dortmund, Germany, 2003.