Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (3): 32-38.doi: 10.6040/j.issn.1672-3961.0.2017.426

• Machine Learning & Data Mining • Previous Articles     Next Articles

A method of multi-sensor data fusion under the complicated environment

Mingming TIAN(),Jihua YE*(),Shimin WANG,Yejing WAN   

  1. College of Computer Information and Engineering, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
  • Received:2017-08-29 Online:2019-06-20 Published:2019-06-27
  • Contact: Jihua YE E-mail:734375913@qq.com;yjhwcl@163.com
  • Supported by:
    国家自然科学基金资助项目(61462042);国家自然科学基金资助项目(61650105);江西省研究生创新专项资金资助项目(YC2016-S170)

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Abstract:

The existing methods do not use the reliability information of the source of evidence data collection, a multi-sensor data fusion algorithm based on the temperature data in complex environment was proposed. It proceeded from the sensor data source, analyzed the evidence source information, evaluated the confidence measure, and revised the conflict evidence with the confidence measure. In the evidence fusion moment, we used iterative fusion method to revise and fusion evidence until the fusion result convergence. Compared with other fusion methods, this method was effective and had better results in the question of evidence conflict.

Key words: multi-sensor, data fusion, wisdom agriculture, iteration, node confidence

CLC Number: 

  • TP23

Fig.1

Membership function of triangle-shape"

Table 1

Five sampling data of the sensor during the period"

℃
传感器 1次 2次 3次 4次 5次
1 19.32 19.16 18.79 18.44 18.94
2 18.37 19.04 19.76 19.93 18.58
3 18.92 18.70 18.68 19.43 18.05

Table 2

Original evidence and D-S results"

传感器 证据
1 (0, 0.36, 0.64) (0, 0.78, 0.32) (0.42, 0.58, 0) (1, 0, 0) (0.12, 0.88, 0)
2 (1, 0, 0) (0, 0.92, 0.08) (0.48, 0.52, 0) (0, 0, 1) (0.84, 0.16, 0)
3 (0.16, 0.84, 0) (0.6, 0.4, 0) (0.74, 0.36, 0) (0, 0.14, 0.86) (1, 0, 0)
D-S融合结果 无法计算 (0, 1, 0) (0.58, 0.42, 0) 无法计算 (1, 0, 0)

Table 3

The modified evidence and D-S results"

传感器 证据
1 (0, 0.320 4,
0.569 6, 0.11)		 (0, 0.694 2,
0.284, 0.11)		 (0.373 8, 0.516 2,
0, 0.11)		 (0.89, 0,
0, 0.11)		 (0.106 8, 0.783 2,
0, 0.11)
2 (0.66, 0,
0, 0.34)		 (0, 0.607 2, 0.052 8,
0.34)		 (0.316 8, 0.343 2,
0, 0.34)		 (0, 0, 0.66,
0.34)		 (0.554 4, 0.105 6,
0, 0.34)
3 (0.124 8, 0.655 2,
0, 0.22)		 (0.468, 0.312,
0, 0.22)		 (0.577 2, 0.280 8,
0, 0.22)		 (0, 0.109 2,
0.670 8, 0.22)		 (0.78, 0,
0, 0.22)
修正证据结果 (0.148 3, 0.598,
0.212 7, 0.041)		 (0.039, 0.885,
0.057 7, 0.018 3)		 (0.533 6, 0.448 5,
0, 0.017 9)		 (0.394 8, 0.024 2,
0.532 3, 0.048 8)		 (0.679 5, 0.290 4,
0, 0.030 1)

Table 4

Fusion results of different methods"

融合证据 D-S方法 Yager方法 王亮方法 胡海亮方法 本研究方法
m12(A, B, C, Θ) (0.02, 0.95,
0.03, 0.0012)		 (0.006, 0.53,
0.012, 0.452)		 (0.012, 0.965,
0.014)		 (0.012, 0.981,
0.009)		 (0.011, 0.983,
0.008)
m123(A, B, C, Θ) (0.025, 0.97,
0.001, 0)		 (0.003, 0.24,
0, 0.757)		 (0.021, 0.979,
0.001)		 (0.012, 0.981,
0.009)		 (0.013, 0.99,
0.0003)
m1234(A, B, C, Θ) (0.13, 0.86,
0.01, 0)		 (0.001, 0.006,
0, 0.993)		 (0.033, 0.94,
0.027)		 (0.012, 0.99,
0.0001)		 (0.02, 0.975,
0.005)
m12345(A, B, C, Θ) (0.24, 0.75,
0, 0)		 (0.000 8, 0.001 7,
0, 0.997 5)		 (0.078, 0.932,
0)		 (0.051,
0.949, 0)		 (0.032, 0.968, 0)

Table 5

Estimated results of different methods"

方法 D-S方法 王亮方法 胡海亮方法 本研究方法
结果估计 17.65 18.15 19.84 18.68
与真实值误差 1.35 0.75 0.84 0.32

Fig.2

The iterations and accuracy"

1 徐凯.基于物联网的农业环境监控系统研究开发[D].无锡:江南大学, 2013.
XU Kai. Research and development of the agricultural environment monitoring system based on internet of things[D]. Wuxi: Jiangnan University, 2013.
2 熊彦铭, 杨战平. 受证据理论启发的传感器数据融合算法[J]. 华中科技大学学报(自然科学版), 2011, 39 (10): 50- 54.
XIONG Yanming , YANG Zhanping . Data fusion algorithm inspired by evidence theory[J]. Journal of Huazhong University of Science and Technology(Nature Science), 2011, 39 (10): 50- 54.
3 DEMPSTER A P . Upper and lower probabilities induced by a multivalued mapping[J]. The Annals of Mathematical Statistics, 1967, 38 (2): 325- 339.
doi: 10.1214/aoms/1177698950
4 向阳辉, 张干清, 庞佑霞, 等. 多源信息的加权证据理论融合识别方法[J]. 机械科学与技术, 2016, 35 (3): 381- 385.
XIANG Yanghui , ZHANG Ganqing , PANG Youxia , et al. A weighted fusion method for recognizing multi-source information based on weighted evidence theory[J]. Mechanical Science and Technology for Aerospace Engineering, 2016, 35 (3): 381- 385.
5 卢正才, 覃征. 证据合成的一般框架及高度冲突证据合成方法[J]. 清华大学学报(自然科学版), 2011, 51 (11): 1701- 1705, 1716.
LU Zhengcai , QIN Zheng . General framework for evidence combination and its approach to highly conflicting evidence fusion[J]. Journal of Tsinghua University(Science and Technology), 2011, 51 (11): 1701- 1705, 1716.
6 陈炜军, 景占荣, 袁芳菲, 等. D-S证据理论的不足及其数学修正[J]. 中北大学学报(自然科学版), 2010, 31 (2): 161- 168.
doi: 10.3969/j.issn.1673-3193.2010.02.015
CHEN Weijun , JING Zhanrong , YUAN Fangfei , et al. Shortcoming of D-S evidence theory and its mathematics modification[J]. Journal of North University of China(Natural Science Edition), 2010, 31 (2): 161- 168.
doi: 10.3969/j.issn.1673-3193.2010.02.015
7 YAGGER R R . On the dempster-shafer framework and new combination rules[J]. Information Sciences, 1987, 41 (2): 93- 137.
doi: 10.1016/0020-0255(87)90007-7
8 MURPHY C K . Combining belief functions when evidence conflicts[J]. Decision Support Systems, 2000, 29 (1): 1- 9.
9 王亮, 吕卫民, 滕克难, 等. 基于分类修正的多证据合成方法[J]. 控制与决策, 2015, 30 (1): 125- 130.
WANG Liang , LYU Weimin , TENG Kenan , et al. Combination method of multi-evidence based on classification correction[J]. Control and Decision, 2015, 30 (1): 125- 130.
10 叶继华, 聂小斯. 改进证据分类合成方法在农作物生长环境评估中的应用[J]. 数据采集与处理, 2015, 30 (6): 1196- 1204.
YE Jihua , NIE Xiaosi . Improved evidence classification synthetic method in environment assessment of crop growth[J]. Journal of Data Acquisition and Processing, 2015, 30 (6): 1196- 1204.
11 胡海亮, 钟求喜, 刘浏, 等. 基于迭代合成的D-S证据理论改进方法[J]. 计算机应用研究, 2016, 33 (10): 2985- 2987, 3044.
doi: 10.3969/j.issn.1001-3695.2016.10.026
HU Hailiang , ZHONG Qiuxi , LIU Liu , et al. Improved method to D-S evidence theory based on iterative synthesis[J]. Application Research of Computers, 2016, 33 (10): 2985- 2987, 3044.
doi: 10.3969/j.issn.1001-3695.2016.10.026
12 杨国宁, 冯秀芳. D-S证据理论中冲突证据融合新方法[J]. 计算机应用与软件, 2014, 31 (2): 82- 85.
doi: 10.3969/j.issn.1000-386x.2014.02.022
YANG Guoning , FENG Xiufang . A new conflict evidence fusion method in d-s evidence theory[J]. Computer Applications and Software, 2014, 31 (2): 82- 85.
doi: 10.3969/j.issn.1000-386x.2014.02.022
13 尹宝全.农业数据处理中的异常检测方法研究[D].北京:中国农业大学, 2016.
YIN Baoquan. Research on outlier detection approach for agricultural data processing[D]. Beijing: China Agricultural University, 2016.
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