Towards Mathematics, Computers and Environment: A Disasters Perspective
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Published By Springer International Publishing

9783030212049, 9783030212056
Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Bayesian Analysis of the Disaster Damage in Brazil

2019 ◽  
pp. 163-183
Author(s):  
Camila Bertini Martins ◽  
Viviana Aguilar Muñoz ◽  
André Yoshizumi Gomes ◽  
Ricardo Manhães Savii ◽  
Carolina Locatelli Colla
Keyword(s):  
Bayesian Analysis

Digital Humanities and Big Microdata: New Approaches for Demographic Research

2019 ◽  
pp. 217-231
Author(s):  
Pier Francesco De Maria ◽  
Leonardo Tomazeli Duarte ◽  
Álvaro de Oliveira D’Antona ◽  
Cristiano Torezzan
Keyword(s):  
Digital Humanities ◽  
Demographic Research ◽  
New Approaches

About Interfaces Between Machine Learning, Complex Networks, Survivability Analysis, and Disaster Risk Reduction

2019 ◽  
pp. 185-215 ◽  
Author(s):  
Leonardo Bacelar Lima Santos ◽  
Luciana R. Londe ◽  
Tiago José de Carvalho ◽  
Daniel S. Menasché ◽  
Didier A. Vega-Oliveros
Keyword(s):  
Machine Learning ◽  
Complex Networks ◽  
Risk Reduction ◽  
Disaster Risk Reduction ◽  
Disaster Risk

Methodological Proposal for the Prediction of Hydrological Responses to Land-Uses and Land-Cover Changes in a Brazilian Watershed

2019 ◽  
pp. 103-124
Author(s):  
Lidiane dos Santos Lima ◽  
Paulo Cesar Colonna Rosman ◽  
Julia Celia Mercedes Strauch ◽  
Nelson Ferreira Fernandes ◽  
Letícia de Carvalho Giannella
Keyword(s):  
Land Cover ◽  
Land Cover Changes ◽  
Land Uses ◽  
Hydrological Responses

Data Mining Approaches to the Real-Time Monitoring and Early Warning of Convective Weather Using Lightning Data

2019 ◽  
pp. 83-101
Author(s):  
Stephan Stephany ◽  
Cesar Strauss ◽  
Alan James Peixoto Calheiros ◽  
Glauston Roberto Teixeira de Lima ◽  
João Victor Cal Garcia ◽  
...  
Keyword(s):  
Data Mining ◽  
Real Time ◽  
Early Warning ◽  
Real Time Monitoring ◽  
The Real ◽  
Convective Weather ◽  
Monitoring And Early Warning
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