Abstract
This chapter introduces a novel Monte Carlo (MC) technique called Statistical Blockade (SB) which focuses on significantly rare values in the tail distributions of data space. This conjunctive application of machine learning and extreme value theory can provide useful solutions to address the extreme values of hydrological series and thus to enhance modeling of value falls in the ‘Tail End’ of hydrological distributions. A hydrological case study is included in this chapter and the capability of Statistical Blockade is compared with adequately trained Artificial Neural Networks (ANN) and Support Vector Machines (SVM) to get an idea of the accuracy of the Statistical Blockade.
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Remesan, R., Mathew, J. (2015). Application of Statistical Blockade in Hydrology. In: Hydrological Data Driven Modelling. Earth Systems Data and Models, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-09235-5_8
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DOI: https://doi.org/10.1007/978-3-319-09235-5_8
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