GDP prediction of The Gambia using generative adversarial networks.

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Tác giả: Alieu Gibba, Herbert Imboga, Haruna Jallow, Ronald Waweru Mwangi

Ngôn ngữ: eng

Ký hiệu phân loại: 296.311 God

Thông tin xuất bản: Switzerland : Frontiers in artificial intelligence , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 725089

Predicting Gross Domestic Product (GDP) is one of the most crucial tasks in analyzing a nation's economy and growth. The primary goal of this study is to forecast GDP using factors such as government spending, inflation, official development aid, remittance inflows, and Foreign Direct Investment (FDI). Additionally, the paper aims to provide an alternative perspective to Generative Adversarial Networks method and demonstrate how such deep learning technique can enhance the accuracy of GDP predictions with small data and economy like The Gambia. We proposed the implementation of Generative Adversarial Networks to predict GDP using various economic factors over the period from 1970 to 2022. Performance metrics, including the coefficient of determination R
1. Gdp
2. Prediction
3. Of
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