【摘要】 分类器集成是一种解决复杂模式识别问题的有效方法,它通过形成一组分类器并将它们的结果进行组合,可以显著地提高分类系统的泛化推广能力。论文将分类器集成技术用于核爆地震信号的模式识别,并以前馈神经网络作基分类器为例,研究了不同的分类器个体生成方法和决策形成规则对识别效果的影响。更多还原

【Abstract】 As a powerful solution to difficul t pattern recognition problem,classifier ensemble can significantly improve the e xtensibility of classifying systems through training a finite number of classif iers and combining their results.In this paper,classifier ensemble is used to classify nuclear explosion and nature earthquake by the seismic recording.Take the forward-feed neural network as an example,the generation methods of differ ent classifier and the influences of the deci-sion formation rule on the recog nition effect are analyzed.更多还原