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Software component retrieval is the core part in software development methodology based on component. In the paper, particle swarm optimization algorithm and RBF neural network is presented to software component retrieval. Radial basis function neural network which is simplified as RBFNN is a kind of feed forward neural network, which encounters the local optimization problems. particle swarm optimization algorithm is applied to select appropriate parameters in the radial basis function neural network. The case data are applied to prove the performance of the method proposed in the paper. By the experimental analysis, the software component retrieval model based on PSO-RBF neural network is feasible and effective.