Estimation of conventional and innovative models for Rwanda's GDP per capita: A comparative analysis of artificial neural networks and Box–Jenkins methodologies

Estimation of conventional and innovative models for Rwanda's GDP per capita: A comparative analysis of artificial neural networks and Box–Jenkins methodologies

This study aims to model the time series data of Rwanda's GDP per capita using the Box–Jenkins (BJ) approach as a conventional approach and artificial neural networks (ANNs) as an innovative approach. The BJ technique, which utilizes autoregressive moving average - ARMA or an integrated version...

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Bibliographic Details
Main Authors: İsmail Yenilmez, Fabrice Mugenzi
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:Scientific African
Subjects:
Box–Jenkins
Artificial neural networks
Long short-term model
Generalized regression neural network
Multilayer perceptron
GDP per capita
Online Access:http://www.sciencedirect.com/science/article/pii/S2468227623003575

Internet

http://www.sciencedirect.com/science/article/pii/S2468227623003575

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