Abstract
Bangladesh is the most populous country on the planet. We recognized Bangladesh as an independent sovereign country, yet despite its large population, Bangladesh lags far behind the world’s wealthiest nations. In the developed world, especially in terms of economics, a country’s Gross Domestic Product (GDP) is the monetary value of all completed labor and products produced within its borders during a period. It is concerned with the overall measurement of all financial transactions. In this research, we use a machine learning time series ARIMA model to correctly estimate the Bangladesh GDP Growth Rate with the order of (0, 1, 1). The auto ARIMA function generates a minimal AIC value, which is used to verify the model. The SARIMAX (0, 1,1, 6) model can predict the GDP with 87.51% accuracy. We implement this machine learning time series ARIMA model on the web application; GDP indicator. Users may find the GDP growth rate for Bangladesh in the future here, as well as watch our country’s upcoming economy.
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Shohug, M.M.H., Bitto, A.K., Rubi, M.A., Bijoy, M.H.I., Rahaman, A. (2023). A Data-Driven Approach to Forecasting Bangladesh Next-Generation Economy. In: Singh, P., Singh, D., Tiwari, V., Misra, S. (eds) Machine Learning and Computational Intelligence Techniques for Data Engineering. MISP 2022. Lecture Notes in Electrical Engineering, vol 998. Springer, Singapore. https://doi.org/10.1007/978-981-99-0047-3_6
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DOI: https://doi.org/10.1007/978-981-99-0047-3_6
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