基于SVM的多传感器信息融合算法

支持向量机(Support Vector machine,简称SVM)是一种基于结构风险最小化原理,具有很高泛化性能的学习算法。针对工业多传感器测控系统中,被测系数与相关参数之间存在有较大的非线性和模糊关系,提出了一种基于支持SVM的多传感器信息融合模型及算法。为小样本、非线性、高维数一类多传感器信息融合问题的建模提供了一种有效的途径。通过对“纸张水份在线测量系统”应用表明,基于SVM的多传感器信息融合模型及算法在测量精度和推广性能上都具有一定的优越性。

A Algorithm of Multiple Sensor Information Fusion Based on SVM

The support vector machine (SVM) is an algorithm based on structure risk minimizing principle and having high generalization ability. In the course of multiple sensor information fusion of industrial control, sensor has bigger nonlinearity and fuzzy relation between coefficient and relevant parameter, A kind of model and algorithm of multiple sensor information fusion based on the support vector machine are proposed. The model offered a kind of effective way for little sample, non-linear, high dimension. Through use to "paper moisture content online measuring system", the model and algorithm have certain superiority in measuring precision and performance of popularizing.