Assessing machine learning techniques in forecasting lumpy skin disease occurrence based on meteorological and geospatial features-Reference-Cited by-同舟云学术

Assessing machine learning techniques in forecasting lumpy skin disease occurrence based on meteorological and geospatial features

Published:2022-01-14 Issue:1 Volume:54 Page:
ISSN:0049-4747
Container-title:Tropical Animal Health and Production
language:en
Short-container-title:Trop Anim Health Prod

Author:

Afshari Safavi Ehsanallah^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Animal Science and Zoology,Food Animals

Link

https://link.springer.com/content/pdf/10.1007/s11250-022-03073-2.pdf

Reference53 articles.

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3. Alemayehu, G., Zewde, G., & Admassu, B. (2013). Risk assessments of lumpy skin diseases in Borena bull market chain and its implication for livelihoods and international trade. Tropical Animal Health and Production, 45(5), 1153–1159. https://doi.org/10.1007/s11250-012-0340-9

4. Alkhamis, M. A., & VanderWaal, K. (2016). Spatial and temporal epidemiology of lumpy skin disease in the Middle East, 2012–2015. Frontiers in veterinary science, 3, 19. https://doi.org/10.3389/fvets.2016.00019

5. Allepuz, A., Casal, J., & Beltrán‐Alcrudo, D. (2019). Spatial analysis of lumpy skin disease in Eurasia—Predicting areas at risk for further spread within the region. Transboundary and emerging diseases, 66(2), 813-822. https://doi.org/10.1111/tbed.13090

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