基于粗糙集解决BP网络模式识别中的噪声

为了解决BP网络模式识别中的噪声问题,提出了利用粗糙集的上、下近似和边界线集理论对噪声样本进行处理的方法。该方法对处于下近似集内的含噪声属性值,将噪声消除后转换为理想状态下的属性值;对处于边界域内的含噪声属性值保持不变。当属性值处于边界域内属性的个数与全部属性数的比值达到某个确定的值时,就认为该样本受到噪声干扰过大,对其拒绝识别。通过实验对比表明,该方法能有效地降低BP网络模式识别的误识率。

Solution to Noise Problem of BP Network for Pattern Recognition Based on RS Theory

In order to solve the noise problem of BP network for pattern recognition,the paper proposes a method to process the noisy samples based on the upper approximations,the lower approximations and the boundary region theories of rough sets.The method eliminates the noise of attribute values and changes them into ideal values when they are in the lower approximations;and those attribute values with noise will remain unchanged while they are in the boundary region.The sample will be refused to recognize if the p...