本文针对数据聚类分析和最优化问题的相似点，用模拟退火算法进行聚类分析。

In view of the similarities between data clustering analysis and optimization questions, this paper deals with data clustering analysis by using simulation anneal algorithms.

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最后本文用模拟退火算法来优化测试调度，实验结果表明此算法调度的测试时间要比报道的结果都好。

Simulated annealing algorithm is used to get the optimum test solution, and it demonstrates its advantage over other solution published recently in test time.

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用模拟退火算法改进BP神经网络，克服了BP神经网络极易陷入局部最优点的缺点，进一步提高了网络的性能。

Improving BP neural network with simulated annealing algorithm can overcome the defect of falling into local optimal point easily, and further improve the network performance.

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