Abstract: A soft sensor modeling method is presented which selects optimal fuzzy rules by tuning the radius of a subtractive cluster center. Subtractive clustering is used to generate a T-S fuzzy model. Secondly, the radius of a cluster center is adjusted to select optimal fuzzy rules, to acquire a fuzzy model with perfect generalization capability. The parameters is fine-tuned by means of a hybrid gradient descent (GD) and least-squares estimation (LSE). Finally, the method is used to model a PDU naphtha's dry point and the result shows that it can determine the optimal model fastly and achieve satisfactory prediction precision.