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...

Cijeli opis

Bibliografski detalji

Glavni autori:	Irene Nandutu, Marcellin Atemkeng, Nokubonga Mgqatsa, Sakayo Toadoum Sari, Patrice Okouma, Rockefeller Rockefeller, Theophilus Ansah-Narh, Jean Louis Ebongue Kedieng Fendji, Franklin Tchakounte
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2022-10-01
Serija:	Mathematics
Teme:	SARIMAX SARIMAX-LSTM modeling LSTM neural networks wildlife
Online pristup:	https://www.mdpi.com/2227-7390/10/21/3988
Oznake:	Dodaj oznaku Bez oznaka, Budi prvi tko označuje ovaj zapis!