School of Computing

Publications by Mr Sam Cramer

Also view these in the Kent Academic Repository

Article
Cramer, S. et al. (2017). An extensive evaluation of seven machine learning methods for rainfall prediction in weather derivatives. Expert Systems with Applications [Online] 85:169-181. Available at: https://doi.org/10.1016/j.eswa.2017.05.029.
Alexandridis, A., Kampouridis, M. and Cramer, S. (2017). A Comparison between Wavelet Networks and Genetic Programming in the Context of Temperature Derivatives. International Journal of Forecasting [Online] 33:21-47. Available at: http://www.sciencedirect.com/science/article/pii/S0169207016300711.
Conference or workshop item
Cramer, S. et al. (2017). Pricing Rainfall Based Futures Using Genetic Programming. in: 20th European Conference, EvoApplications: European Conference on the Applications of Evolutionary Computation. Springer, pp. 17-33. Available at: http://dx.doi.org/10.1007%2F978-3-319-55849-3_2.
Cramer, S. et al. (2016). Predicting Rainfall in the Context of Rainfall Derivatives Using Genetic Programming. in: IEEE Computational Intelligence for Financial Engineering & Economics, Symposium Series on Computational Intelligence. IEEE, pp. 711-718. Available at: https://doi.org/10.1109/SSCI.2015.108.
Cramer, S., Kampouridis, M. and Freitas, A. (2016). Feature Engineering for Improving Financial Derivatives-based Rainfall Prediction. in: IEEE World Congress on Evolutionary Computation.
Cramer, S., Kampouridis, M. and Freitas, A. (2016). A Genetic Decomposition Algorithm for Predicting Rainfall within Financial Weather Derivatives. in: Genetic and Evolutionary Computation Conference (GECCO 2016).
Cramer, S. and Kampouridis, M. (2015). Optimising the deployment of fibre optics using Guided Local Search. in: IEEE Congress on Evolutionary Computation (CEC).. Available at: http://www.cec2015.org/.
Total publications in KAR: 7 [See all in KAR]

School of Computing, University of Kent, Canterbury, Kent, CT2 7NF

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Last Updated: 20/10/2017