The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.
TY - CONF AU - Maheshwari, M. AU - Dunning, D.J. AU - Jones, J.K. AU - King, M.P. AU - Kockelbergh, H.R. AU - Pollard, A.E. ED - Liu, Lin ED - Byrd, John M. ED - Neuenschwander, Regis T. ED - Picoreti, Renan ED - Schaa, Volker R. W. TI - Prediction and Clustering of Longitudinal Phase Space Images and Machine Parameters Using Neural Networks and K-Means Algorithm J2 - Proc. of IPAC2021, Campinas, SP, Brazil, 24-28 May 2021 CY - Campinas, SP, Brazil T2 - International Particle Accelerator Conference T3 - 12 LA - english AB - Machine learning algorithms were used for image and parameter recognition and generation with the aim to optimise the CLARA facility at Daresbury, using start-to-end simulation data. Convolutional and fully connected neural networks were trained using TensorFlow-Keras for different instances, with examples including predicting Longitudinal Phase Space (LPS) images with machine parameters as input and FEL parameter prediction (e.g. pulse energy) from LPS images. The K-means clustering algorithm was used to cluster the LPS images to highlight patterns within the data. Machine learning techniques can enhance the way large amounts of data are processed and analysed and so have great potential for application in accelerator science R&D. PB - JACoW Publishing CP - Geneva, Switzerland SP - 3417 EP - 3420 KW - FEL KW - network KW - simulation KW - electron KW - ECR DA - 2021/08 PY - 2021 SN - 2673-5490 SN - 978-3-95450-214-1 DO - doi:10.18429/JACoW-IPAC2021-WEPAB318 UR - https://jacow.org/ipac2021/papers/wepab318.pdf ER -