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Innovative Applications of Artificial Neural Networks in Tax Forecasting
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Advisor(s)
Abstract(s)
A importância da previsão das receitas fiscais é vital para o planeamento econômico e sustentabilidade financeira em Moçambique. Este estudo aborda este tópico explorando o potencial das Redes Neurais Artificiais (RNAs) para melhorar tais previsões. O problema central é a limitação dos métodos convencionais em captar a complexidade dos dados fiscais. A razão para a adoção de RNAs reside na sua superior capacidade de modelação e previsão em ambientes de dados grandes e complexos. Os resultados obtidos demonstram que as RNAs podem prever as receitas fiscais com maior precisão, superando os modelos tradicionais. A conclusão aponta para a RNA como uma ferramenta valiosa para as autoridades fiscais, aumentando a eficiência na cobrança e contribuindo para a estabilidade fiscal do país.
The importance of forecasting tax revenues is vital for economic planning and financial sustainability in Mozambique. This study addresses this topic by exploring the potential of Artificial Neural Networks (ANNs) to improve such forecasts. The central problem is the limitation of conventional methods in capturing the complexity of tax data. The rationale for adopting ANNs lies in their superior modeling and forecasting capacity in large and complex data environments. The results obtained demonstrate that ANNs can forecast tax revenues with greater accuracy, outperforming traditional models. The conclusion points to ANNs as a valuable tool for tax authorities, increasing collection efficiency and contributing to the country's fiscal stability.
The importance of forecasting tax revenues is vital for economic planning and financial sustainability in Mozambique. This study addresses this topic by exploring the potential of Artificial Neural Networks (ANNs) to improve such forecasts. The central problem is the limitation of conventional methods in capturing the complexity of tax data. The rationale for adopting ANNs lies in their superior modeling and forecasting capacity in large and complex data environments. The results obtained demonstrate that ANNs can forecast tax revenues with greater accuracy, outperforming traditional models. The conclusion points to ANNs as a valuable tool for tax authorities, increasing collection efficiency and contributing to the country's fiscal stability.
Description
Keywords
Neural networks Tax forecast Sustainability
Citation
Rodolfo, Bruno Couto de Abreu; Gonçalves, Bruno F. (2025). Innovative Applications of Artificial Neural Networks in Tax Forecasting. Navus - Revista de Gestão e Tecnologia. ISSN 2237-4558. 16, p. 1-18
Publisher
Navus - Revista de Gestão e Tecnologia