Journal Articles

• Reich, T., Hulbert, D. and Budka, M., 2022. A Model Architecture for Public Transport Networks Using a Combination of a Recurrent Neural Network Encoder Library and a Attention Mechanism. Algorithms, 15 (9).
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• Reich, T., Budka, M. and David, H., 2021. Bus journey simulation to develop public transport predictive algorithms. Soft Computing Letters.
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• Reich, T., Bancroft, A. and Budka, M., 2021. EP11 Using machine learning to recover unrecorded prehospital data. Emergency Medicine Journal, 38 (9), A5-A6.
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• Reich, T. and Budka, M., 2019. Proof of concept for a syndromic surveillance system based on routine ambulance records in the South West of England, for the influenza season 2016/2017. Br Paramed J, 4 (2), 22-30.
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Conferences

• Reich, T., Budka, M. and Hulbert, D., 2020. Impact of Data Quality and Target Representation on Predictions for Urban Bus Networks. 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, 2843-2852.
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Theses

• Reich, T., 2022. Sequence modelling using deep learning approaches for spatiotemporal public transport data. PhD Thesis. Bournemouth University, Faculty of Science and Technology.
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