Modeling Dengue vector population using remotely sensed data and machine learning-Reference-Cited by-同舟云学术

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Modeling Dengue vector population using remotely sensed data and machine learning

Published:2018-09 Issue: Volume:185 Page:167-175
ISSN:0001-706X
Container-title:Acta Tropica
language:en
Short-container-title:Acta Tropica

Author:

Scavuzzo Juan M.,Trucco Francisco,Espinosa Manuel,Tauro Carolina B.,Abril Marcelo,Scavuzzo Carlos M.,Frery Alejandro C.

Publisher

Elsevier BV

Subject

Infectious Diseases,Parasitology,Insect Science,Veterinary (miscalleneous)

Reference53 articles.

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2. Spatial and temporal dynamics of Aedes aegypti larval sites in Bello, Colombia;Arboleda;J. Vector Ecol.,2012

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4. ANFIS-based approach for predicting sediment transport in clean sewer;Azamathulla;Appl. Soft Comput. J.,2012

5. Spiking neural networks for crop yield estimation based on spatiotemporal analysis of image time series;Bose;IEEE Trans. Geosci. Remote Sens.,2016

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