Design and implementation of system of information fusion based on evidence theory

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (4): 11-13.

• 博士论坛 • Previous Articles Next Articles

Design and implementation of system of information fusion based on evidence theory

LUO He^1,2,FU Chao²,HU Xiao-jian²

1.School of Computer & Information，Hefei University of Technology，Hefei 230009，China
2.Institute of Computer and Network Systems，Hefei University of Technology，Hefei 230009，China

Received:2007-09-19 Revised:2007-11-07 Online:2008-02-01 Published:2008-02-01
Contact: LUO He

基于证据理论的信息融合系统设计与实现

罗贺^1,2,付超²,胡小建²

1.合肥工业大学计算机与信息学院，合肥 230009
2.合肥工业大学计算机网络系统研究所，合肥 230009

通讯作者: 罗贺

Abstract

Abstract: In order to fuse incomplete information from multi-sensors，a method of information fusion based on the evidence theory is proposed in the paper.The new combination rule is suggested by introducing neural network technique into it.On this basis，the object-oriented software design and development method is used to analyze the software architecture and build different functional modules.In the end，the system of information fusion based on the evidence theory is developed by Visual C++ 6.0.

Key words: information fusion, evidence theory, system design

摘要： 为了对多传感器获取的不完整信息进行融合，提出了基于证据理论的信息融合方法，并将神经网络技术引入到证据合成规则中，建立了新的合成规则。在此基础上，采用面向对象的系统设计开发方法，分析了系统的体系结构，建立了各功能模块，并利用Visual C++ 6.0开发了基于证据理论的信息融合系统。

关键词: 信息融合, 证据理论, 系统设计

LUO He^1,2,FU Chao²,HU Xiao-jian². Design and implementation of system of information fusion based on evidence theory[J]. Computer Engineering and Applications, 2008, 44(4): 11-13.

罗贺^1,2,付超²,胡小建². 基于证据理论的信息融合系统设计与实现[J]. 计算机工程与应用, 2008, 44(4): 11-13.

[1]	LIU Chang, QIU Weigen, ZHANG Lichen. Person Re-identification Based on Deformable Mask Alignment Convolution Model [J]. Computer Engineering and Applications, 2021, 57(5): 146-152.
[2]	JIANG Bin, LIANG Xiao’an, ZHANG Liang, GAO Yangjun. Evidence Combination Method Based on Improved Modified Weight [J]. Computer Engineering and Applications, 2021, 57(24): 100-106.
[3]	CHEN Kunfeng, PAN Zhisong, WANG Jiabao, SHI Lei, ZHANG Jin, JIAO Shanshan. Collaborative Learning Method for Cross Modality Person Re-identification [J]. Computer Engineering and Applications, 2021, 57(12): 115-125.
[4]	ZHANG Hong, CHENG Chuanqi, XU Zhigang, LI Jianhua. Survey of Data Fusion Based on Deep Learning [J]. Computer Engineering and Applications, 2020, 56(24): 1-11.
[5]	LIU Xiaoya, WANG Yingming. Research on Personal Credit Scoring Based on SVM Ensemble [J]. Computer Engineering and Applications, 2020, 56(14): 272-278.
[6]	HAN Erdong. Research Progress on Multi-criteria Decision Making Method Based on Probabilistic Linguistic Term Set [J]. Computer Engineering and Applications, 2020, 56(10): 27-35.
[7]	RUAN Kai, QIU Weigen. Study on Facial Expression Recognition Algorithm of Multi-Information Fusion Based on Deep Learning [J]. Computer Engineering and Applications, 2019, 55(5): 192-196.
[8]	LUO Lan, XIAO Jianyu. Conflict Evidence Synthesis Method of Effective Discount Evidence Sources [J]. Computer Engineering and Applications, 2019, 55(4): 154-158.
[9]	LI Guo, MA Chunyang, MA Jianxiao. Fusion Fault Diagnosis Using DPCA & Improved Evidence Theory [J]. Computer Engineering and Applications, 2019, 55(20): 197-201.
[10]	CHEN Jinguang1，2, WANG Xinghui1，2, MA Lili1，2, ZHANG Xindong1，2, GONG Linming1，2. Cardinalized Probability Hypothesis Density Smoother Using Piece-wise RTS [J]. Computer Engineering and Applications, 2019, 55(1): 50-55.
[11]	YAN Zhijun, TAO Yang. Conflict evidence combination rule based on uncertainty measurement and evidence distance [J]. Computer Engineering and Applications, 2018, 54(10): 54-58.
[12]	CHEN Fuqiang1, ZHOU Xuecheng1，2, LI Yihai1, YANG Zishang1, WANG Gaofeng1, YAN Lulu1. Design and implementation of plant root 3D architecture measurement system [J]. Computer Engineering and Applications, 2018, 54(10): 249-255.
[13]	TU Shijie1，2, CHEN Hang1, FENG Gang2. Using evidence theory and fuzzy function to identify ballistic target [J]. Computer Engineering and Applications, 2017, 53(6): 169-173.
[14]	DUAN Suolin, YANG Ke, MAO Dan, REN Juepeng. Fuzzy evidence theory-based algorithm in application of fire detection [J]. Computer Engineering and Applications, 2017, 53(5): 231-235.
[15]	HUANG Jiacheng1, YAN Tao1, YAO Miao2, SONG Jiayou2. Research on measurement uncertainty evaluation method of small sample automatic test system [J]. Computer Engineering and Applications, 2017, 53(20): 214-218.

Design and implementation of system of information fusion based on evidence theory

基于证据理论的信息融合系统设计与实现

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics