Indian Crop Yield Prediction using LSTM Deep Learning Networks
Sony M Kuriakose, Tripty Singh
Abstract
Farming is considered as the backbone of our country, so it is very important to introduces new facilities that would magnify farming. Finding the type of crop that farmers could sow would improve yield will be helpful for them. Research is being conducted in this area supporting our ideology. In our work, we would propose to help the farmers identify the type of crop which would produce a good yield for a particular season by taking account of Soil type, Soil fertility, Climatic conditions, Rainfall, Individual seed required conditions In our model we used Deep Learning techniques to predict the yield or success rate with the help of the given data for different places. In Phase 1 we predicted the future climatic conditions and rainfall (in mm) using various machine learning algorithms on the pre-processed data. In Phase 2 we predicted the success rate for different crops considering the soil inputs and climate inputs. And obtained crop success rate for different crops, thus maximizing the yield at a place.