Rice Crop Yield Prediction Study by Artificial Intellegence Techniques

Every country has agriculture as a vital factor for development in every field and so whole domestic fully depends upon it. Rice Crop‘s analysis fully depends upon the market rate of the rice, quantity produced and the quality of the rice with yield. Rice crop yield also depends upon the various suggestions and monitoring the production of crops timely. Monitoring of the crop in a timeframe with crop yield prediction gives an output in automatic manner by Artificial intelligence (AI). A study was done after analyzing some artificial intelligence techniques as Deep Learning (DL) with its hybrid approaches using Recurrent Neural Network (RNN), Deep Neural Network (DNN) and Artificial Neural Network (ANN). These techniques become helpful for identification and improvement in the rice crop yield prediction. It was observed that by analyzing the requirement of hybrid network approach and recurrent neural network approach gives a very useful idea for prediction of rice crop yield. A comparison was done after study and discussed the performance of convolutional neural network and artificial neural network. Analysis was done after discussing the outcomes from the study and also set the perspectives for future from the final optimized results.