A kernel-based strategy to design Convolutional Neural Network Architecture for learning spatial and temporal representation of weather variables

A kernel-based strategy to design Convolutional Neural Network Architecture for learning spatial and temporal representation of weather variables

Even though there exists no universal deﬁnition for extreme precipitation events, they can be referred to the period of time in which empirical rainfall thresholds are abruptly exceeded. Therefore, their timely forecasting is of great interest for decision makers from many ﬁelds, such as: urban plan...

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Bibliografski detalji
Glavni autor:	González Vergara, Juan Fernando (author)
Format:	bachelorThesis
Jezik:	eng
Izdano:	2021
Teme:	Basado en datos Pronóstico inmediato Precipitación extrema Ingeniería de características Aprendizaje profundo Data-driven Nowcasting Extreme precipitation Feature selection Feature engineering Deep learning
Online pristup:	http://repositorio.yachaytech.edu.ec/handle/123456789/388
Oznake:	Dodaj oznaku Bez oznaka, Budi prvi tko označuje ovaj zapis!

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