Forecasting Tea Production in the Context of Bangladesh Utilizing Machine Learning

A Al Ryan, SK Shuvessa, S Mamun… - 2023 14th …, 2023 - ieeexplore.ieee.org
One of the most popular drinks, second only to water, is tea. Bangladesh ranks as the
world's 10th-largest manufacturer of tea. Tea has a big impact on poverty reduction, rural …

Harvesting Insights: Unveiling the Future of Mango Yield Using Real-Time Bangladesh Climate Data by Supervised Machine Learning Approach

MMR Sarker, MS Ahamed, LB Iqbal… - 2023 14th …, 2023 - ieeexplore.ieee.org
Mango, a unique fruit of the Indian subcontinent, was cultivated under the supervision of
Mughal emperor Akbar [1]. Its exceptional taste impressed Alexander the Great [2] …

Airline Sentiments Unplugged: Leveraging Deep Learning for Customer Insights

HD Arpita, A Al Ryan, MS Hossen… - 2023 5th International …, 2023 - ieeexplore.ieee.org
Over the past twenty years, the competitive airline industry has expanded at an exponential
rate. As more people travel through various airlines, they encounter more amenities and …

Predicting Sugarcane Yields using Supervised Learning: A Comparative Study

PA Papon, MM Rahman, S Ahamed… - 2023 14th …, 2023 - ieeexplore.ieee.org
Bangladesh's sole source of white sugar is sugarcane, an agricultural commodity used to
produce biofuels and other products. In recent years, ML techniques have been used to …

GingerBangla: A Supervised Machine Learning Approach for Predicting Ginger Yield using Bangladeshi Climate Data

LB Iqbal, L Rukhsara, MMR Sarker… - 2023 14th International …, 2023 - ieeexplore.ieee.org
Ginger (Zingiber officinale) farming is an important part of Bangladesh's agriculture, and it
also contributes significantly to the country's economy. Accurate prediction of ginger yield is …