Publicação

Innovative Applications of Artificial Neural Networks in Tax Forecasting

Detalhes bibliográficos
Resumo:	The importance of forecasting tax revenues is vital for economic planning and financial sustainability in Mozambique. The study addresses this topic by exploring the potential of Artificial Neural Networks (ANNs) to improve such predictions. The central problem is the limitation of conventional methods in capturing the complexity of fiscal data. The objective is to develop an ANN model that incorporates historical data and economic factors, providing a mixed methodology that enriches the analysis with qualitative and quantitative data. The rationale for adopting ANNs lies in their superior modeling and prediction capabilities in large and complex data environments. The results achieved demonstrate that ANNs can predict tax revenues with greater accuracy, surpassing traditional models. The conclusion points to the ANN as a valuable tool for tax authorities, enhancing efficiency in collection and contributing to the country's fiscal stability.
Autores principais:	Rodolfo, Bruno Couto de Abreu
Outros Autores:	Gonçalves, Bruno F.
Assunto:	Neural networks Tax forecast Sustainability
Ano:	2025
País:	Portugal
Tipo de documento:	artigo
Tipo de acesso:	acesso aberto
Instituição associada:	Instituto Politécnico de Bragança
Idioma:	inglês
Origem:	Biblioteca Digital do IPB

Descrição
Resumo:	The importance of forecasting tax revenues is vital for economic planning and financial sustainability in Mozambique. The study addresses this topic by exploring the potential of Artificial Neural Networks (ANNs) to improve such predictions. The central problem is the limitation of conventional methods in capturing the complexity of fiscal data. The objective is to develop an ANN model that incorporates historical data and economic factors, providing a mixed methodology that enriches the analysis with qualitative and quantitative data. The rationale for adopting ANNs lies in their superior modeling and prediction capabilities in large and complex data environments. The results achieved demonstrate that ANNs can predict tax revenues with greater accuracy, surpassing traditional models. The conclusion points to the ANN as a valuable tool for tax authorities, enhancing efficiency in collection and contributing to the country's fiscal stability.