| 王龙辉,高嵩,屈星.基于SVM的核电站环境辐射监测网络中传感器节点缺失值估计算法[J].南华大学学报(自然科学版),2012,26(4):14~17.[WANG Long-hui1,GAO Song2,QU Xing2.SVM Based Missing Data Imputation Algorithm in Nuclear Power Plants Environmental Radiation Monitor Sensor Network[J].Journal of University of South China(Science and Technology),2012,26(4):14~17.] |
| 基于SVM的核电站环境辐射监测网络中传感器节点缺失值估计算法 |
| SVM Based Missing Data Imputation Algorithm in Nuclear Power Plants Environmental Radiation Monitor Sensor Network |
| 投稿时间：2012-11-07 |
| DOI： |
| 中文关键词: 核电站 环境辐射监测 缺失值 估计算法 支持向量机 |
| 英文关键词:nuclear power plant environmental radiation monitor missing data imputation algorithm SVM |
| 基金项目:湖南省科技厅科研基金资助项目（2012FJ4332) |
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| 中文摘要: |
| 传感器节点监测数据缺失会影响核电站外围环境辐射监测的有效性，需要对缺失数据进行准确估计.提出一种基于支持向量机的监测数据缺失值估计算法，对传感器节点缺失监测数据进行估计.用实际监测数据对算法进行了验证，用均方误差和相关系数评价实验结果.并与现有的基于神经网络的估计算法进行了性能比较.实验结果表明，本文所提出的算法具有较高的估计精度. |
| 英文摘要: |
| Monitor data mission in sensor node will influence the validity of environmental radiation monitoring around a nuclear power plant.To solve the problem,a missing data imputation algorithm based on support vector machine(SVM) is proposed to impute the missing data.This Algorithm is validated with real radiation monitoring data,evaluated by using MSE and correlation coefficient and compared with ANN based imputation algorithm.The experimental results demonstrate that the proposed algorithm can achieve higher imputation accuracy. |
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