Zobrazeno 1 - 6
of 6
pro vyhledávání: '"André D. L. Zanchetta"'
Autor:
Nicolás Velásquez, Ricardo Mantilla, Witold Krajewski, Felipe Quintero, André D. L. Zanchetta
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 14, Iss 7, Pp n/a-n/a (2022)
Abstract We present a novel approach to determine spatially distributed routing parameters for the distributed hydrological Hillslope Link Model (HLM), an ordinary differential equations‐based streamflow forecasting model implemented and tested in
Externí odkaz:
https://doaj.org/article/63ae6aef65eb4b6f8cc514783f17e2f7
Publikováno v:
Forecasting, Vol 4, Iss 1, Pp 126-148 (2022)
Timely generation of accurate and reliable forecasts of flash flood events is of paramount importance for flood early warning systems in urban areas. Although physically based models are able to provide realistic reproductions of fast-developing inun
Externí odkaz:
https://doaj.org/article/5bd4ee8543c744ec89d0dba96840b36d
Autor:
Kleber X. S Souza, André D. L Zanchetta, S. M. F. S. Massruhá, Raphael Ricciotti, Helano Póvoas de Lima
Publikováno v:
7th World Congress on Computers in Agriculture Conference Proceedings, 22-24 June 2009, Reno, Nevada.
In this paper a tool called Diagtext is presented. This tool aims to help the process of extraction of information from textual documents by identifying groups of similar documents in such a way that an expert can decide which category a document wou
Publikováno v:
Hydrology, Vol 9, Iss 12, p 216 (2022)
The use of machine learning (ML) for predicting high river flow events is gaining prominence and among its non-trivial design decisions is the definition of the quantitative precipitation estimate (QPE) product included in the input dataset. This stu
Externí odkaz:
https://doaj.org/article/7149383f157d42f892005309f0e4f834
Publikováno v:
Geosciences, Vol 12, Iss 11, p 426 (2022)
The use of data-driven surrogate models to produce deterministic flood inundation maps in a timely manner has been investigated and proposed as an additional component for flood early warning systems. This study explores the potential of such surroga
Externí odkaz:
https://doaj.org/article/68e52fad42784cfe80dbbfc2ceb5414d
Publikováno v:
Water, Vol 12, Iss 2, p 570 (2020)
Recent years have witnessed considerable developments in multiple fields with the potential to enhance our capability of forecasting pluvial flash floods, one of the most costly environmental hazards in terms of both property damage and loss of life.
Externí odkaz:
https://doaj.org/article/e96c7006de714b8c8ba7dc95f48e3751