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A data fusion algorithm based on self-adaptive weighted estimation in farmland WSN

文献类型： 会议论文

第一作者： Desheng Li

作者： Desheng Li 1 ; Huarui Wu 2 ; Feifei Li 2 ; Yisheng Miao 2 ;

作者机构： 1.School of Science, Beijing University of Civil Engineering and Architecture

2.Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences

关键词： Wireless sensor networks;Data fusion;Relative distance;Adaptive weighting

会议名称： International Conference on Management Innovation and Information Technology

主办单位：

页码： 427-434

摘要： There are several uncertain factors in the farmland wireless sensor networks data collection, such as complex environment, sensor measurement error, and data missing in both time and space dimension. This paper proposed a self-adaptive weighted fusion scheme to improve the data accuracy of farmland wireless sensor networks. This paper calculated relative Euclidean distances as data weight of each multiple sampling data and picked out error data based on this data weight. After all the large error data had been excluded according to the data correlation degree, data fusion based on the data weight within the effective data is realized. Data fusion is more effective by introducing the weight mentioned above. Experiment shows that the self-adaptive weighted fusion scheme has a higher accuracy and efficiency than the existing methods.

分类号： G20-53

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