A New Combination Rule of Evidence Theory on Multi-Source Information Fusion

2017 ◽  
Author(s):  
Xu-Hui Lan ◽  
Ling-Zhi Li ◽  
Yong-Min Guo ◽  
Chang-Xi Li
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
New Combination ◽  
Combination Rule ◽  
Source Information

Fault Diagnosis of Engine Based on Improved Dempster-Shafer Information Fusion Method

2009 ◽  
Vol 16-19 ◽  
pp. 1310-1317
Author(s):  
Wei Zhou ◽  
Ying Ji Liu ◽  
Qing Fu Cao ◽  
Tian Xia Zhang
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Combination Method ◽  
New Combination ◽  
Fusion Technology ◽  
Combination Rule ◽  
Experiment Research ◽  
New Approach ◽  
Weight Value

In order to enhance the accuracy of engine fault diagnosis, information fusion technology was applied and a novel combination method is proposed based on D-S evidence theory. The evidence groups were classified by evidence conflict coefficient, the importance of each highly conflict evidence was calculated, and the credibility of each evidence was determined with a distance function of evidence bodies. Then the weight value of each evidence was revised with its importance and credibility respectively. Finally, the Dempster combination rule was used to realize the information fusion. The effectiveness of the new approach proposed was verified by theoretical analysis and experiment research results. Comparing with D-S evidence theory and the improved synthesis formula, the new combination method is more efficient in improving the accuracy and the certainty degree of engine fault diagnosis.

Research on Evaluation of Vehicle Dangerous Traveling State Based on Information Fusion Method

2013 ◽  
Vol 791-793 ◽  
pp. 1018-1022
Author(s):  
Peng Wang ◽  
Zhi Qiang Liu
Keyword(s):  
Information Fusion ◽  
Evaluation System ◽  
Evidence Theory ◽  
Recognition System ◽  
Fusion Method ◽  
Source Information ◽  
State Recognition ◽  
Research On Evaluation ◽  
Lane Departure ◽  
Level Information

An evaluation system of vehicle traveling state was proposed,and an unsafe vehicle traveling state recognition system was established using multi-level information fusion method. In view of the effects of the complexity of the driving environment, a variety of working conditions and the diversity of vehicle traveling characteristics, combing BP neural network with Dempster-Shafer evidence theory technique, the multi-information decision-level fusion was proposed to estimate the different kind model of the vehicle status. To verify the proposed strategies,the vehicle traveling posture evaluation system was established. The lane departure parameters and the relative distance parameters were studied in order to get the characterization of the vehicle traveling status information. The simulation results indicate that the adaptability and accuracy and the intelligence level of driving characterization estimation are significantly improved by using the pattern classification and decision technology of multi-source information fusion.

scholarly journals An Extended Base Belief Function in Dempster–Shafer Evidence Theory and Its Application in Conflict Data Fusion

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2137
Author(s):  
Dingyi Gan ◽  
Bin Yang ◽  
Yongchuan Tang
Keyword(s):  
Data Fusion ◽  
Data Management ◽  
Information Fusion ◽  
Evidence Theory ◽  
Belief Function ◽  
Mass Function ◽  
Combination Rule ◽  
Basic Probability ◽  
Belief Entropy ◽  
Management Method

The Dempster–Shafer evidence theory has been widely applied in the field of information fusion. However, when the collected evidence data are highly conflicting, the Dempster combination rule (DCR) fails to produce intuitive results most of the time. In order to solve this problem, the base belief function is proposed to modify the basic probability assignment (BPA) in the exhaustive frame of discernment (FOD). However, in the non-exhaustive FOD, the mass function value of the empty set is nonzero, which makes the base belief function no longer applicable. In this paper, considering the influence of the size of the FOD and the mass function value of the empty set, a new belief function named the extended base belief function (EBBF) is proposed. This method can modify the BPA in the non-exhaustive FOD and obtain intuitive fusion results by taking into account the characteristics of the non-exhaustive FOD. In addition, the EBBF can degenerate into the base belief function in the exhaustive FOD. At the same time, by calculating the belief entropy of the modified BPA, we find that the value of belief entropy is higher than before. Belief entropy is used to measure the uncertainty of information, which can show the conflict more intuitively. The increase of the value of entropy belief is the consequence of conflict. This paper also designs an improved conflict data management method based on the EBBF to verify the rationality and effectiveness of the proposed method.

scholarly journals Innovative assessment scheme of navigation risk based on improved multi-source information fusion techniques

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877254
Author(s):  
Bo Li ◽  
Fuwen Pang
Keyword(s):  
Information Fusion ◽  
Time Complexity ◽  
Euclidean Distance ◽  
Evidence Theory ◽  
Classification Model ◽  
Support Vector ◽  
Source Information ◽  
Distance Ratio ◽  
Slack Variable ◽  
Nonlinear Support

To deal with highly time complexity and unstable assessments for conflicting evidences from various navigation factors, we put forward an innovative assessment scheme of navigation risk based on the improved multi-source information fusion techniques. Different from the existing studies, we first deduce the nonlinear support vector machine classification model for the general scenario. The slack variable is adaptively computed based on the Euclidean distance ratio. Considering the unsatisfactory characteristics of the standard Dempster–Shafer evidence theory, the optimal combination rule is derived step by step. What"s more, the lowly dimensional Kalman filter is applied to forecast the navigation risk. Simultaneously, the time complexity of each technique is analyzed. With respect to the vessel navigation risk, the assessment results are provided to indicate the reliability and efficiency of the proposed scheme.

A Network Security Situational Awareness Model Based on Information Fusion

2013 ◽  
Vol 846-847 ◽  
pp. 1632-1635
Author(s):  
Abasi
Keyword(s):  
Network Security ◽  
Information Fusion ◽  
Situational Awareness ◽  
Evidence Theory ◽  
Arma Model ◽  
Situational Factors ◽  
Source Information ◽  
Network Nodes ◽  
Model Based ◽  
The Future

Security situational awareness has become a hot topic in the area of network securityresearch in recent years. The existing security situational awareness methods are analyzed and compared in details, and thus a newnetwork security situational awareness model based on information fusion is proposed. This modelfuses multi-source information from a mass of logs by introducing the modified D-S evidence theory,gets the values of nodes security situational awareness by situational factors fusion using attacks threat,and vulnerability information which network nodes have and successful attacks depend on, computesthe value of network security situational awareness by nodes situation fusion using service informationof the network nodes, and draws the security-situation-graph of network. Then, it analyzes the timeseries of the computing results by ARMA model to forecast the future threat in network security.Finally an example of actual network datasets is given to validate the network security situationalawareness model and algorithm. The results show that this model and algorithm is more effective andaccurate than the existing security situational awareness methods.

Research Based on Information Fusion of Safety Risks Prediction and Control Management in Construction

2011 ◽  
Vol 480-481 ◽  
pp. 1502-1506
Author(s):  
Ping Zhao ◽  
Hu Zhang
Keyword(s):  
Information Fusion ◽  
Construction Projects ◽  
Evidence Theory ◽  
Construction Safety ◽  
Source Information ◽  
Accident Rate ◽  
Safety Risks ◽  
Prediction And Control ◽  
Hazard Sources ◽  
And Control

Safety risks management of safety potential information and hazard sources has been taken in Construction process. It is the most important measure to solve the current situation that safety accidents is frequent in Chinese Construction projects. The main reasons of frequent accidents were find out and the D-S evidence theory of multi-source information fusion method was used to reduce the accident rate in Construction safety in this paper. Through analyzing and predicting the engineering data and information in human, machine, environment and management four aspects in Construction, prediction model was built in Construction safety risks management, the possibility of dangerous and harmful level in the construction project can be known, preventive measures for specific situations were taken and promptly the safety state of the Construction will be ensured.

scholarly journals A Weighted Evidence Combination Method Based on the Pignistic Probability Distance and Deng Entropy

2020 ◽  
Author(s):  
Lifan Sun ◽  
Yuting Chang ◽  
Jiexin Pu ◽  
Haofang Yu ◽  
Zhe Yang
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
Combination Method ◽  
Uncertain Information ◽  
Combination Rule ◽  
Simulation Experiments ◽  
Sensor Information ◽  
Bodies Of Evidence ◽  
Probability Distance ◽  
Deng Entropy

The Dempster-Shafer (D-S) theory is widely applied in various fields involved with multi-sensor information fusion for radar target tracking, which offers a useful tool for decision-making. However, the application of D-S evidence theory has some limitations when evidences are conflicting. This paper proposed a new method combining the Pignistic probability distance and the Deng entropy to address the problem. First, the Pignistic probability distance is applied to measure the conflict degree of evidences. Then, the uncertain information is measured by introducing the Deng entropy. Finally, the evidence correction factor is calculated for modifying the bodies of evidence, and the Dempster’s combination rule is adopted for evidence fusion. Simulation experiments illustrate the effectiveness of the proposed method dealing with conflicting evidences.

A Research on the Improved Information Fusion Algorithm

2014 ◽  
Vol 543-547 ◽  
pp. 1909-1912
Author(s):  
Guo Dong Zhang ◽  
Rui Min Qi
Keyword(s):  
Decision Making ◽  
Information Fusion ◽  
Evidence Theory ◽  
Source Information ◽  
Fusion Algorithm ◽  
Mutually Independent

In the field of information confusion, evidence theory takes advantage of its uncertainties. But in practical evidences are always mutually independent, However, multi-source information fusion is a comprehensive integration and then obtaining decision-making, sometimes the result of information fusion give us wrong conclusion. So an improved information fusion algorithm is proposed in this paper. It can heighten the information confusion reliability and accuracy in a practical example.

Application of D-S Theory in Information Fusion of Water Quality Measurement Sensors

2012 ◽  
Vol 241-244 ◽  
pp. 956-959 ◽  
Author(s):  
Hai Feng Li ◽  
Hui Zuo ◽  
Xu Feng Hua
Keyword(s):  
Information Fusion ◽  
Measurement System ◽  
Evidence Theory ◽  
Quality Measurement ◽  
Fusion Rule ◽  
Combination Rule ◽  
Sensor Measurement ◽  
System Information ◽  
Water Quality Measurement ◽  
Main Factor

This paper issues the D-S evidence theory and modifies the fusion rule according to the relation of time and the NH3 content in water. A few concepts of D-S evidence theory and D-S evidence combination rule are presented. The modified D-S algorithm is simulated in time and space fusion of multi-sensor measurement system information. It could distinguish the main factor that changing the NH3 content in water. The measurement system cost could be decreased.

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