Crop yield prediction in agriculture based on climatic conditions and ground water level prediction for southern regions

The main aim of this project is to predict the rainfall ,ground water level and temperature for next ten years to predict the crop yield. The prediction of crop yield based on previous years downfall, temperature and ground water level results in taking necessary steps to improve crop yield in future years.Understanding crop yield can help ensure food security and reduce impacts of climate change. Crops are sensitive to various weather phenomena such as temperature, weather and rainfall. Therefore, it becomes crucial to incorporate these features when predicting the yield of a crop. Forecasting is a complicated process. In this work, ARMA (Auto Regressive Moving Average) method is employed to forecast crop yield. Past ten years of knowledge set is taken for temperature, rainfall and ground water level for our country. Moreover, classification of downfall, temperature and ground water level data set records is done using ANN approach to predict the model for future test record data sets. It will be helpful in analyzing crop yield in the past and so as to predict the future levels