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Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms,lds using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integra

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On Geostatistical Analysis of Rainfall Using Data from Boundary Sites,. Two datasets were considered: the first one comprised 232 climatic stations within Galicia and the second one consisted of 322 rain gauges including the former 232 from Galicia and adding 90 stations from boundary provinces (42 from Asturias, 31 from León and 17 from Zamora). Total monthly rainfal

弓箭

Geostatistics Applied to the City of Porto Urban Climatology,gn, performed by a measuring/recording appliance installed in a bus that maneuvered through a given path (established . in such a way that spatial variability within the city could be accounted for). In order to model such data by geostatistical techniques, a two step approach was adopted. The first

马具

Integrating Meteorological Dynamic Data and Historical Data into a Stochastic Model for Predicting ire risk maps. Daily Severity Rating (DSR), a meteorological risk of forest fire index, from the Canadian Forest Fire Weather Index System (CFFWIS), results from the transformation of daily weather observations into relatively simple indices that can be used to predict fire occurrence, behaviour and

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