Crop Yield Prediction Through Artificial Neural Networks
Pradeep Kumar Kushwaha, Ajay Rana, Swati Vashisht, Vangala Sri Vaathsav, Smiksh Rakesh Shan, Garima Bhardwaj
Abstract
Evolving technologies like Artificial Intelligence, Machine Learning and Data Science are being integrated with almost all sectors. Agriculture, being one of the primary sectors is a no exception to this. Regular technological advancements happening in the agricultural field ensures food security and economical balance in the country. Variety of parameters like soil type, rainfall, temperature, market price influence the yield of a crop. Having dependable information about previous crop yield patterns is essential for making assessments on agricultural risk management and predicting yields. Predicting crop yields is a difficult task for the decision makers. A good crop yield forecast model might be adopted by farmers the choice of what and when to plant. The increasing population with changing environmental conditions impact the crop yield. This paper discusses a model that predicts the Crop Yield through Neural Networks which is an important part of the Machine Learning.