Radial basis function model for vegetable price prediction

The Agricultural sector needs more support for its development in developing countries like India. Price prediction helps the farmers and also the Government to make effective decision. Based on the complexity of vegetable price prediction, making use of the characteristics of data mining classification technique like neural networks such as self-adapt, self-study and high fault tolerance, to build up the model of Back-propagation neural network (BPNN) and Radial basis function neural network (RBF) to predict vegetable price. A prediction models were set up by applying the BPNN and RBF neural networks. Taking tomato as an example, the parameters of the model are analysed through experiment. Compare the two neural network forecast results. The result shows that the RBF neural network is more efficient and accurate than Back-propagation neural network.