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Data fusion technology is widely utilized in energy constraint wireless sensor network (WSN) to reduce the amount of messages exchanged between sensor nodes. However, there are many similarities between wireless sensor network and artificial neural network. In this paper we present a neural data fusion algorithm based on PCA to classify the states of environment. The results attained by experiments show that the algorithm proposed in this paper can reduce the data transmission in WSN effectively and implement classification of different types of parameters simply and practicably.