The application of an improved BP artificial neural network in distributed data mining

Distributed data mining (DDM) technique is becoming necessary for large and multi-scenario datasets requiring resource, which are heterogeneous and distributed. In this paper, we focused on distributed data of tax and the artificial neural network (ANN). Here we used an improved ANN to make a classification of tax data, first we use a set of sample data to train the improved ANN, so it could get a group of weights and then we could use the weights to make classification. From experiments we know it could reduce the training time and improve the classification accuracy.