dc.description.abstract |
Rice is the staple food of Bangladesh's 135 million people. It accounts for nearly half of all rural
jobs, two-thirds of the total calorie supply, and one-half of total protein intake for the average
person in the region. In Bangladesh, the rice sector accounts for half of the agricultural GDP and
one-sixth of national income. Rice is grown by nearly all of the country's 13 million farm families.
Rice is grown on approximately 10.5 million hectares, a figure that has remained nearly constant
over the last three decades. Rice is cultivated on about 75% of the total cropped area and over 80%
of the total irrigated area. As a result, rice is critical to the Bangladeshi people's survival. In our
paper, we have worked on different types of rice. They are- Aus, Aman and Boro. We also worked
with potatoes. Potato is a major tuber crop in Bangladesh. Potatoes can lower the risk of
hypertension, stroke, increases antioxidant activity and prevent diseases. During the winter, potato
is widely grown in all of Bangladesh's districts. During 1997-98, 1,36,332 ha of land were used
for potato cultivation. To feed its 135 million inhabitants of Bangladesh, it is important to predict
the yield of these major crops accurately. There are some weather parameters including humidity,
temperature, sunshine, cloud coverage influences the yield of crops. Thus, in our study, we aim to
predict yield of rice (Aus, Aman, Boro) and potato utilizing Data mining and Machine learning
techniques.
We applied 6 regression algorithms to predict the Yield of these crops. We have used- Gradient
Boosting Regression, Neural Network Regression, Decision Tree Regression, Random Forest
Regression, SVM, Linear Regression and Lasso Regression. Our study also shows that Gradient
boosting Regression algorithm performs better than the other six algorithms used in this study to
predict the yield of Rice and Potato. Our study will be a baseline study for future work to predict
the yield of cereal crops (e.g., rice, and wheat) and potato in Bangladesh. |
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