基于模糊C-均值的原型模式选择及其在核爆地震识别中的应用

协同模式识别是一种全新的有着抗噪声、抗缺损等诸多优良特性的模式识别方法,但将其用于核爆地震和天然地震的分类时,采用现有的原型模式选择方法识别效果并不理想.本文提出了一种基于模糊C-均值的原型模式选择方法,该方法首先对每一类训练样本采用模糊C-均值聚类的方法聚为c类,然后选取这c类的c个重心或c个聚类中心作为该类的原型模式进行核爆地震的协同模式识别.实验结果表明,同现有的原型模式选择方法相比,该方法使识别率有了较大提高.

Prototype Selection Based on FCM and Its Application in Discrimination between Nuclear Explosion and Earthquake

The synergetic pattern recognition is a new way of pattern recognition with many excellent features such as noise resistance and deformity resistance.But when it is used in the discrimination between nuclear explosion and earthquake using existing methods of prototype selection,the results are not satisfying.A new method of prototype selection based on FCM is proposed in this paper.First,each group of training samples is clustered into c groups using FCM;then c barycenters or centers are chosen as prototypes.Experiment results show that compared with existing methods of prototype selection this new method is effective and it increases the recognition ratio greatly.