Published Paper Details:

ABSTRACT The advancement in the field of agriculture is more essential to forecast the yield loss and the drought monitoring to discover possible intervention areas. The machine learning models plays a vital role in the process of agriculture to detect the anomaly of droughts to avoid the crop yield loss by monitoring rainfall, temperature and moisture. Though there are many prediction models are available, deep knowledge about the pattern of climatic condition is very essential to improve the drought prediction. Thus, this paper concentrated on developing an enriched prediction model which optimize the performance of the Deep Neural Network by inducing the intelligence of the eagle strategy to fine tune the parameters values which influence the accuracy of prediction model. The simulation results proved that the Enriched Eagle Strategy based Deep Neural Network predict the presence of Drought in eight different districts all over India, compared to the other conventional prediction models.