Merging computational fluid dynamics and machine learning to reveal animal migration strategies-Reference-Cited by-同舟云学术

Merging computational fluid dynamics and machine learning to reveal animal migration strategies

Published:2021-05-20 Issue:7 Volume:12 Page:1186-1200
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Olivetti Simone¹^ORCID,Gil Michael A.¹²,Sridharan Vamsi K.¹^ORCID,Hein Andrew M.¹³^ORCID,Shepard Emily

Affiliation:

1. Southwest Fisheries Science Center National Oceanic and Atmospheric AdministrationInstitute of Marine SciencesUniversity of California Santa Cruz CA USA

2. Department of Ecology and Evolutionary Biology University of Colorado Boulder CO USA

3. Department of Ecology and Evolutionary Biology University of California Santa Cruz CA USA

Funder

California Department of Fish and Wildlife

National Oceanic and Atmospheric Administration

Publisher

Wiley

Subject

Ecological Modelling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13604

Reference72 articles.

1. Convergent patterns of long-distance nocturnal migration in noctuid moths and passerine birds

2. When Is Migration Worthwhile for Animals That Walk, Swim or Fly?

3. An LSTM network for highway trajectory prediction

4. Mean free-path length theory of predator–prey interactions: Application to juvenile salmon migration

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