AI for Yield Prediction in Corn under Soil Moisture Stress
This case study shows an application of AI for yield prediction under stress and specifically drought stress. The complexity of farming data such as irrigation and precipitation patterns, makes AI a good candidate to deal with such data. Here we applied an AI technique calls DTW to predict yield of corn. The intuition behind this technique is that if we can find a farming season that is most similar to this season mathematically, then the crop yield should be similar too and we can predict it with high accuracy.