基于区间证据理论的多传感器数据融合水质判断方法

周剑; 马晨昊; 刘林峰; 孙力娟; 肖甫

doi:10.11959/j.issn.1000-436x.2016174

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基于区间证据理论的多传感器数据融合水质判断方法

学术论文 | 更新时间：2024-06-05

- 基于区间证据理论的多传感器数据融合水质判断方法
- Multi-sensor data fusion method for water quality evaluation based on interval evidence theory
- 通信学报 2016年37卷第9期页码：20-29
- 作者机构：
  
  1. 南京邮电大学计算机学院，江苏南京 210023
  2. 江苏省无线传感网高技术研究重点实验室，江苏南京210023
- 作者简介：
  
  [ "周剑（1984-），男，江苏扬州人，南京邮电大学副教授，主要研究方向为传感器网络、数据融合。" ]
  [ "马晨昊（1990-），男，河南新乡人，南京邮电大学硕士生，主要研究方向为数据融合。" ]
  [ "刘林峰（1981-），男，江苏丹阳人，南京邮电大学副教授，主要研究方向为传感器网络。" ]
  [ "孙力娟（1963-），女，江苏南京人，南京邮电大学教授，主要研究方向为传感器网络。" ]
  [ "肖甫（1980-），男，湖南邵阳人，南京邮电大学教授，主要研究方向为传感器网络。" ]
- 基金信息：
  
  国家自然科学基金资助项目(71301081);国家自然科学基金资助项目(61373139);国家自然科学基金资助项目(61572261);国家自然科学基金资助项目(61300165);国家自然科学基金资助项目(61302157);江苏省自然科学基金资助项目(BK20130877);江苏省自然科学基金资助项目(BK20140895);国家博士后基金资助项目(2014M551637);江苏省博士后基金资助项目(1401046C);南京邮电大学引进人才基金资助项目(NY213035)
- DOI：10.11959/j.issn.1000-436x.2016174
  中图分类号： TP393
- 网络出版日期：2016-09，
  
  纸质出版日期：2016-09-25
- 稿件说明：
移动端阅览
周剑, 马晨昊, 刘林峰, 等. 基于区间证据理论的多传感器数据融合水质判断方法[J]. 通信学报, 2016,37(9):20-29.

Jian ZHOU, Chen-hao MA, Lin-feng LIU, et al. Multi-sensor data fusion method for water quality evaluation based on interval evidence theory[J]. Journal on communications, 2016, 37(9): 20-29.
周剑, 马晨昊, 刘林峰, 等. 基于区间证据理论的多传感器数据融合水质判断方法[J]. 通信学报, 2016,37(9):20-29. DOI： 10.11959/j.issn.1000-436x.2016174.

Jian ZHOU, Chen-hao MA, Lin-feng LIU, et al. Multi-sensor data fusion method for water quality evaluation based on interval evidence theory[J]. Journal on communications, 2016, 37(9): 20-29. DOI： 10.11959/j.issn.1000-436x.2016174.

摘要

针对传感网测量水质数据过程中存在的必然不确定性和随机不确定性，提出了一种基于区间证据理论的多传感器数据融合水质判断方法。考虑传感器精度误差以及测量数据异常等问题，将每个传感器测量的水质数据用区间数表示，通过计算水质数据与每个水质等级特征值之间的距离，得到判断水质等级的区间证据。按照区间证据组合规则将多传感器的区间证据融合成综合区间证据，最后根据决策准则，由综合区间证据判断水质等级。实验表明，该方法能够从不确定水质数据中准确判断水质等级。

Abstract

For the inevitable uncertainty and random uncertainty in the process of measuring water quality data with the sensor network

a multi-sensor data fusion method for water quality evaluation based on interval evidence theory was proposed.Considering the precision error of sensor and the abnormalities of measured data

every water quality data measured by sensor was represented by interval number.By calculating the distance between the water quality data and the features of each water quality class

the interval evidence of water quality class was acquired.According to the interval evidence combining rule

a comprehensive interval evidence was obtained by combining the interval evidence of each sensor.Finally

the water quality class was determined based on the comprehensive interval evidence by the decision rule.Experiments show that the proposed method can evaluate water quality class more accurately from the uncertain water quality data.

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references

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