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To improve the difference existed in the link prediction accuracy and adaptability of different topology structure similarity based methods,a neural network-based link prediction algorithm,which fused similarity indices by neural network was proposed.The algorithm uses neural network to study the numerical characteristics of different similarity indices,and uses particle swarm optimization to optimize the neural network,and calculates the fusion index by the optimized neural network model.The experiment on the real network data set shows that the prediction accuracy of the algorithm is obviously higher than that before the fusion,and the accuracy is better than the existing methods.