Abstract: Fuzzy C-means clustering (FCM) algorithm is a method that often used in data pretreatment, but it can bring the problem on interference between border information at the same time, so the accuracy of model can′t be improved a lot. Linear discriminant analysis (LDA) is an effective method used to expand the limits of the samples which can make clustering more precise. The combination of FCM and improved LDA is applied to SVM by multimodels method, which can reinforce the algorithm. The application in the soft sensor modeling of BPA shows that this method has a certain practicality.