Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6592912 | Chinese Journal of Chemical Engineering | 2018 | 7 Pages |
Abstract
The problem of designing a model for the sludge volume index (SVI) is addressed in this paper. This model is realized by means of a multivariate local quadratic polynomial regression (MLQPR) method, in which, a quadratic polynomial regression function is established to describe the relationship between SVI and the relative variables. Then, the important terms of the quadratic polynomial regression function are determined by the significant test of the corresponding coefficients. Moreover, a local estimation method is introduced to adjust the weights of the quadratic polynomial regression function to improve the accuracy of the model.228
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Honggui Han, Xiaolong Wu, Luming Ge, Junfei Qiao,