Nonlinear Spline Kernel-based Partial Least Squares Regression Method and Its Application

Inspired by the traditional Wold＇s nonlinear PLS algorithm comprises of NIPALS approach and a spline inner function model, a novel nonlinear partial least squares algorithm based on spline kernel （named SK-PLS ） is proposed for nonlinear modeling in the presence of multicollinearity. Based on the inner-product kernel spanned by the spline basis functions with infinite number of nodes, this method firstly maps the input data into a highdimensional feature space, and then calculates a linear PLS model with reformed NIPALS procedure in the feature space and gives a unified framework of traditional PLS ＂kernel＂ algorithms in consequence. The linear PLS in the feature Space corresponds to a nonlinear PLS in the original input （primal） space. The good approximating property of spline kernel function enhances the generalization ability of the novel model, and two numerical experiments are given to illustrate the feasibility of the proposed method.     

反应蒸馏塔内催化剂不同装填方式的液固传质效率

采用苯甲酸颗粒-水-空气系统,进行了气液两相逆流状态下的传质实验,获得了规整装填和散堆装填两种不同装填方式对液固传质系数的影响。分析得出在载点以下的操作范围内,气液逆流反应蒸馏塔内液相雷诺数的变化对传质影响较大,气相雷诺数的影响则不明显;并且散堆装填的液固接触效率明显好于规整装填,两者效率之比为1．72倍,并采用液固接触效率关联了传质Sherwood数,得到了如下关联结果：Sh／Sc^1/3=4．65Ф^1.1ReL^0.245。     

A Novel Extension of Kernel Partial Least Squares Regression

Based on continuum power regression(CPR) method, a novel derivation of kernel partial least squares(named CPR-KPLS) regression is proposed for approximating arbitrary nonlinear functions.Kernel function is used to map the input variables(input space) into a Reproducing Kernel Hilbert Space(so called feature space),where a linear CPR-PLS is constructed based on the projection of explanatory variables to latent variables(components). The linear CPR-PLS in the high-dimensional feature space corresponds to a no...     

以填料结构为模型参数的填料塔泛点预测新方法

根据从双膜理论出发由Bernou lli方程得到的液泛气速与液速之间的函数关系,考察了两个与填料有关的模型参数:一个是由填料比表面积a和床层空隙率ε所组成的填料因子a/3ε,另一个是本文定义的填料结构参数。研究表明:拉西环和球形颗粒属于同一类型,其结构参数确定为1.4;而鲍尔环和矩鞍环属于另一类填料,填料结构参数确定为0.9。由于同时考虑了填料结构和填料因子的作用,因此对液泛的预测更有针对性、更加准确。