The Application of Fusion Algorithm Based on Matrix Analysis in Evidence Theory

2014 ◽  
Vol 687-691 ◽  
pp. 1412-1415
Author(s):  
You Zhi Zhang ◽  
Yu Dong Qi ◽  
Han Li Wang
Keyword(s):  
Time Delay ◽  
Information Fusion ◽  
Evidence Theory ◽  
Matrix Analysis ◽  
Fusion Algorithm ◽  
C Language ◽  
Evidence Combination ◽  
Delay Increase ◽  
Recursive Calculation ◽  
Sensor Information

This paper directly adopts evidence reasoning formula to calculate sensor information fusion result. The amount of calculation and calculation time delay increase with the increasing number of target found, uses two recursive calculation ways of evidence combination to calculate results, and proposes a fusion algorithm based on matrix analysis, using matlab software and C language programming to realize the method and calculate by an example. The results prove that the fusion result calculated by the method gets the same result as that of evidence reasoning synthesis formula, but the time needed for calculation will be reduced.

scholarly journals Multi-sensor Information Fusion Method Based on BP Neural Network

2016 ◽  
Vol 12 (05) ◽  
pp. 53 ◽  
Author(s):  
Lin Liandong
Keyword(s):  
Neural Network ◽  
Bayesian Inference ◽  
Information Fusion ◽  
System Development ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Fusion Algorithm ◽  
Temperature Detection ◽  
Posterior Expectation ◽  
Sensor Information

This study aims to solve the problem of multi-sensor information fusion, which is a key issue in the multi-sensor system development. The main innovation of this study is to propose a novel multi-sensor information fusion algorithm based on back propagation neural network and Bayesian inference. In the proposed algorithm, a triple is defined to represent a probability space; thereafter, the Bayesian inference is used to estimate the posterior expectation. Finally, we construct a simulation environment to test the performance of the proposed algorithm. Experimental results demonstrate that the proposed algorithm can significantly enhance the accuracy of temperature detection after fusing the data obtained from different sensors.

scholarly journals Based on Multi-sensor Information Fusion Algorithm of TPMS Research

2012 ◽  
Vol 25 ◽  
pp. 786-792 ◽  
Author(s):  
Zhou Yulan ◽  
Zang Yanhong ◽  
Lin Yahong
Keyword(s):  
Information Fusion ◽  
Fusion Algorithm ◽  
Sensor Information

scholarly journals A Multisource Situation Information Fusion Method Based on Dynamic Evidence Combination

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jing Liu ◽  
ChaoWen Chang ◽  
Yuchen Zhang ◽  
Yongwei Wang
Keyword(s):  
Information Fusion ◽  
Detection Rate ◽  
Evidence Theory ◽  
Fusion Method ◽  
False Detection Rate ◽  
False Detection ◽  
Conflicting Evidence ◽  
Evidence Combination ◽  
Fusion Methods ◽  
Fusion Efficiency

To address the problems of fusion efficiency, detection rate (DR), and false detection rate (FDR) that are associated with existing information fusion methods, a multisource information fusion method featuring dynamic evidence combination based on layer clustering and improved evidence theory is proposed in this study. First, the original alerts are hierarchically clustered and conflicting evidence is eliminated. Then, dynamic evidence combination is applied to fuse the condensed alerts, thereby improving the efficiency and accuracy of the fusion. The experimental results show that the proposed method is superior to current fusion methods in terms of fusion efficiency, DR, and FDR.

scholarly journals A Novel Weighted Complex Evidence Combination with Its Application in Multisource Information Fusion

2021 ◽  
Author(s):  
Huaping He ◽  
Liting He ◽  
Fuyuan Xiao
Keyword(s):  
Complex Plane ◽  
Information Fusion ◽  
Distance Function ◽  
Medical Diagnosis ◽  
Evidence Theory ◽  
Fusion Method ◽  
Numerical Example ◽  
Evidence Combination ◽  
The Impact ◽  
Counterintuitive Result

Abstract With the development of evidence theory, classical Dempster-Shafer evidence theory has been extended to complex plane, called complex evidence theory. However, counterintuitive result may occurs in the case when fusing conflicting complex evidences. To address this problem, a new multisource information fusion method is proposed by means of complex evidential distance function. This proposed method can reduce the impact of abnormal complex evidence on the fusion results to better support decision. A numerical example and an application of medical diagnosis verify the feasibility and effectiveness of the proposed fusion method.

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