Application of support vector machine based on neighborhood rough set to sewage treatment fault diagnoses
Junying Han · Gansu Nongye Daxue xuebao · 2013
In order to automatically diagnose the fault in the sewage treatment proacess,support vector machine based on neighborhood rough set was used.Firstly,data preprocessing was done on training set from three different sides.Secondly,neighborhood rough set was used to find these samples in boundary and to obtain a reduced training set,at the same time,those abnormal samples were deleted.And then,attribute reduction was done and feature weight was imported.Finally support vector machine was trained and tested on the reduction set.The results compared with the others showed that the method not only improved the efficiency of fault diagnosis,but also reduced the complex degree and maintained a better generalization performance.