Rabies Outbreak Prediction Using Deep Learning with Long Short-Term Memory
The purpose of this article is to evaluate the Long Short-Term Memory (LSTM) model performance for rabies outbreak prediction (ROP). Successful forecasting of the initial epidemic outbreaks can decrease the incidence of the ailment and save lives, but this type of research is costly, and an erroneou...
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Main Authors: | Abdulrazak Yahya, Saleh, Shahrulnizam, Medang, Ashraf, Osman Ibrahim |
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Format: | Book Chapter |
Language: | English |
Published: |
Springer Nature Switzerland
2020
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Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/27782/1/Rabies%20Outbreak%20Prediction%20Using%20Deep%20Learning%20with%20Long%20Short-Term%20Memory%20-%20Copy.pdf http://ir.unimas.my/id/eprint/27782/ https://link.springer.com/chapter/10.1007/978-3-030-33582-3_32 |
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