Paper Title :Trade Flow Estimation Between Global Economies Using Machine Learning Techniques
Author :Prateek Rao, Pooshpal Baheti, Rahul Ramesh, Anand M S
Article Citation :Prateek Rao ,Pooshpal Baheti ,Rahul Ramesh ,Anand M S ,
(2023 ) " Trade Flow Estimation Between Global Economies Using Machine Learning Techniques " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 1-5,
Volume-11,Issue-4
Abstract : Bilateral trade flow between global economies has been a critical economic indicator for economists and
policymakers owing to its potential to significantly influence international trade sanctions and policies, which profoundly
impact international relations.This deep-rooted global interdependence has been historically simulated by the international
economy, which engenders substantial mutual benefits for participating companies. The analysis of various economic trends
and the generation of accurate future predictions have become indispensable pursuits since the inception of predictive
machine learning models. By meticulously examining historical economic data and constructing relevant fine-tuned machine
learning models, it is possible to attempt to predict future events and capital flow between countries. The reliable estimation
of bilateral flow is of paramount importance, and the use of machine learning techniques for economic forecasting,
leveraging the unreasonable effectiveness of data, in lieu of traditional statistical methods, can help in achieving exceptional
predictions. In this study, we endeavor to enhance traditional statistical methods by experimenting with several time-agnostic
machine learning models.
Keywords - Artificial Intelligence, Data Mining, Business Analytics, Neural Networks, Gradient Boosting, Bilateral Trade
Flow
Type : Research paper
Published : Volume-11,Issue-4
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-19638
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Copyright: © Institute of Research and Journals
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Published on 2023-07-10 |
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