模拟退火算法在模糊模式识别中的应用研究

本文首先对模糊C-均值聚类作了简要分析和评论，在此基础上将模拟退火机制引入其中，以克服模糊C-均值聚类的局部性和对初始聚类中心的敏感性；然后，采用了基于贴近度和择近原则的模糊识别方法，文中分析了格贴近度的不足之处，并对之进行了改进；最后，详细设计了上述各算法。仿真结果说明，该方法在识别速度和准确率方面都达到了令人满意的效果，为种子的在线检测提供了一种新思路，也拓展了模糊理论的应用范围。

The Fuzzy Pattern Recognition of Maize Seed Based on Simulated Annealing Algorithm

The paper introduces and remarks Fuzzy C-means Clustering firsdy. On the basis of systematic analysis of current algorithms, simulated annealing mechanism is inducted into fuzzy clustering to solve the locality and the sensitiveness of the initial condition of Fuzzy C-means Clustering. Then, this paper proposes the fuzzy discern method based on approximation value and the principle of selecting the near. The deficiency of dose-approximation value is proposed and improved. Finally, the algorithm is designed in detail. Simulation results show that the new method gets a satisfied result both on speed and the correct rate. Thus a new on-line detecting method for the seek is presented. It widens the application of fuzzy theory.