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基于SVM的多传感器信息融合算法
引用本文:周鸣争,汪军. 基于SVM的多传感器信息融合算法[J]. 仪器仪表学报, 2005, 26(4): 407-410
作者姓名:周鸣争  汪军
作者单位:安徽工程科技学院计算机科学与工程系,芜湖,241000
基金项目:安徽省自然科学基金 (0 30 4 2 30 6),安徽省科技厅国际合作基金 (0 2 0 880 0 )资助项目
摘    要: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。

关 键 词:信息融合算法  SVM  多传感器信息融合  信息融合模型  结构风险最小化  Vector  在线测量系统  支持向量机  学习算法  泛化性能  测控系统  模糊关系  纸张水份  推广性能  测量精度  非线性  小样本  高维数
修稿时间:2003-06-01

A Algorithm of Multiple Sensor Information Fusion Based on SVM
Zhou Mingzheng,Wang Jun. A Algorithm of Multiple Sensor Information Fusion Based on SVM[J]. Chinese Journal of Scientific Instrument, 2005, 26(4): 407-410
Authors:Zhou Mingzheng  Wang Jun
Abstract: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.
Keywords:SVM Sensor Information fusion Moisture measurement
本文献已被 CNKI 维普 万方数据 等数据库收录!
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