Rice Blast Disease Prediction Using Integrated SMOTE With Multilayer Perceptron

Abstract

In India, rice blast is a major concern due to favourable weather conditions during the crop season. Climate plays major role in the disease appearance, multiplication, and spread of the fungus. Along with climatic factors, the varieties of seeds also influence the occurrence of rice  blasts, primarily  the  climate  factors  have  a  strong  influence  on  the  occurrence  of  blast  disease  even though a sufficient amount of nutrients are present in the plant. Thus, rice blast disease will occur and develop when certain weather conditions continue for the given period. Forecasting models that make predictions of possible blast disease occurrence may give important information to the producers of rice to manage the disease. Therefore, this project implements the rice blast disease prediction using data balancing technique based multilayer perceptron.