Application of Big Data

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.