A Predictive Analysis on Weather Parameters Based on Bangladesh Agriculture Using Machine Learning Approach

Bangladesh is an agriculture-based country where a large number of people are involved in agricultural activities. A significant portion of the GDP (Gross domestic product) comes from the agricultural sector. Due to the decent weather parameters, the production of agricultural products rate is high in Bangladesh. On the other hand, variation in geographical area, the environmental parameters also vary such as temperature, rainfall, humidity, soil moisture etc. from region to region. So, prediction of these parameters through different machine learning algorithms can surely influence the production rate for crop selection as well as crop yield selection. In this paper, we have applied different machine learning algorithms to predict the three environmental parameters such as temperature, rainfall, relative humidity which has great impact on the environment by using very recent data sets. We have also showed the performance of different machine learning algorithms to get a notable insight of the accuracy of prediction and correlation between these parameters.