Published Paper Details:

Agriculture crop predication is a challenging and interesting problem domain for the computer community. The computer machine helps to improve the productivity of the crop with such predication. This paper illustrates a research model which provides the predications of the wheat crop in the Rajasthan region of India. This paper uses feed forward neural networks models for accomplish the task of predication for the wheat crop. These models are trained with three different feed forward neural networks architectures namely multi layer perception feed forward neural network, generalized regression neural network and radial basis neural network. There is feature scaling method was used for normalization of large previous year's crop detail data which has been obtained by agriculture department of Rajasthan government. The simulation results indicates the better predication with feed forward neural network model trained with Back propagation learning rule in comparison of generalized regression neural network and radial basis neural network.