A Survey on Crop Prediction using Back Propagation Neural Network

The aim of this research is to develop a farmer prediction system to identify crop suitable for particular soil. To achieve this Neural Network should be trained to perform correct prediction for farmers. After the network has been properly trained, it can be used to identify the crop suitable for particular type of soil. The Artificial neural networks are relatively crude electronic networks of "neurons" based on the neural structure of the brain. It process the records one at a time, and "learn" by comparing their prediction of the record with the known actual record. The errors from the initial prediction of the first record is fed back into the network, and used to modify the networks algorithm the second time around and so on for many iterations. An improved Back Propagation Neural Network model with improved learning algorithm provides an effective prediction tool for agriculture crops forecasting. Keywords-Neural Network, Back Propagation, Learning algorithm, Training.