Error Correction Based Deep Neural Networks for Modeling and Predicting South African Wildlife–Vehicle Collision Data

Error Correction Based Deep Neural Networks for Modeling and Predicting South African Wildlife–Vehicle Collision Data

The seasonal autoregressive integrated moving average with exogenous factors (SARIMAX) has shown promising results in modeling small and sparse observed time-series data by capturing linear features using independent and dependent variables. Long short-term memory (LSTM) is a promising neural networ...

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Bibliographic Details
Main Authors: Irene Nandutu, Marcellin Atemkeng, Nokubonga Mgqatsa, Sakayo Toadoum Sari, Patrice Okouma, Rockefeller Rockefeller, Theophilus Ansah-Narh, Jean Louis Ebongue Kedieng Fendji, Franklin Tchakounte
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Mathematics
Subjects:
SARIMAX
SARIMAX-LSTM
modeling
LSTM
neural networks
wildlife
Online Access:https://www.mdpi.com/2227-7390/10/21/3988

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