粗SVM 分类方法及其在污水处理过程中的应用

提出一种基于粗糙集理论和支持向量机理论的粗SVM分类方法，该方法采用粗糙集属性约筒方法以减少属性个数，且在属性约筒过程中选出几组合适的属性集组成新的属性集，使模型具有一定的抗信息丢失能力，同时充分利用SVM的良好推广性能，提高了预测分类精度，对城市污水处理厂运行状态的实验结果表明了该方法的优越性。

Rough support vector machine and its application to wastewater treatment processes

A new classification algorithm named rough support vector machine (RSVM) is presented based on support vector machine (SVM) and rough set theory. RSVM has high predictive classification accuracy with much less attributes, which means less sensors and less cost. And it keeps certain redundant attributes to have high predictive accuracy in the case of lost information caused by sensor fault. RSVM increases classification accuracy with good generalization performance. The numerical experiments for a wastewater treatment process show the effectiveness of the proposed algorithm.