D–S Evidence Theory and its Application in Robot Information Fusion

2011 ◽  
Vol 219-220 ◽  
pp. 799-803
Author(s):  
Yu Sheng Sun ◽  
Cai Ling Zheng ◽  
Ping Ma
Keyword(s):  
Information Fusion ◽  
Autonomous Navigation ◽  
Evidence Theory ◽  
System Control ◽  
Noise Interference ◽  
Laser Sensors ◽  
Control Precision ◽  
Multisensor Information Fusion ◽  
Photoelectric Encoder ◽  
Structure Environment

Multisensor information fusion is wildly treasured and used in the mobile robot field.This thesis describes D–S evidence theory about photoelectric encoder,laser sensors and CCD camera.Because D-S evidence theory allows the existence of uncertainty, we may obtain the event probability according to experience.As a result,it is easier to promote the application.Therefore robot can do autonomous navigation and obstacle aviodance in unknown non-structure environment safely. If the system increased other sensors in the future perfect process,we can also adopt this approach to integration. The experiment results show that the improved D–S evidence theory can eliminate the noise interference,handle signals smoothly and improve the system control precision.

scholarly journals Temporal and Causal Relations on Evidence Theory: an Application on Adverse Drug Reactions

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Luiz Alberto Pereira Afonso Ribeiro ◽  
Ana Cristina Bicharra Garcia ◽  
Paulo Sérgio Medeiros Dos Santos
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
Mass Function ◽  
Data Sources ◽  
Drug Reactions ◽  
Clinical Notes ◽  
Dempster Shafer Theory ◽  
Multisensor Information Fusion ◽  
Shafer Theory ◽  
Theory Of Evidence

The use of big data and information fusion in electronichealth records (EHR) allowed the identification of adversedrug reactions(ADR) through the integration of heteroge-neous sources such as clinical notes (CN), medication pre-scriptions, and pathological examinations. This heterogene-ity of data sources entails the need to address redundancy,conflict, and uncertainty caused by the high dimensionalitypresent in EHR. The use of multisensor information fusion(MSIF) presents an ideal scenario to deal with uncertainty,especially when adding resources of the theory of evidence,also called Dempster–Shafer Theory (DST). In that scenariothere is a challenge which is to specify the attribution of be-lief through the mass function, from the datasets, named basicprobability assignment (BPA). The objective of the presentwork is to create a form of BPA generation using analy-sis of data regarding causal and time relationships betweensources, entities and sensors, not only through correlation, butby causal inference.

scholarly journals Multisensor Fusion Method Based on the Belief Entropy and DS Evidence Theory

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaojing Fan ◽  
Yinjing Guo ◽  
Yuanyuan Ju ◽  
Jiankang Bao ◽  
Wenhong Lyu
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
Case Analysis ◽  
Entire Body ◽  
Combination Rule ◽  
Target Concentration ◽  
Conflicting Evidence ◽  
Multisensor Information Fusion ◽  
Belief Entropy ◽  
Weighted Factor

The Dempster–Shafer evidence theory has been widely applied in multisensor information fusion. Nevertheless, illogical results may occur when fusing highly conflicting evidence. To solve this problem, a new method of the grouping of evidence is proposed in this paper. This method uses a combination of the belief entropy and the degree of conflict of the evidence as the judgment rule and divides the entire body of evidence into two separate groups. For the grouped evidence, both the credibility weighted factor based on the belief entropy function and the support weighted factor based on the Jousselme distance function are taken into consideration. The two determined weighted factors are integrated to adjust the evidence before applying the DS combination rule. Numerical examples are provided to demonstrate the theoretical feasibility and rationality of the proposed method. The fusion results indicate that the proposed method is more accurate than the compared algorithms in handling the paradoxes. A decision-making case analysis of the biological system is performed to validate the practical applicability of the proposed method. The results confirm that the proposed method has the highest belief degree of the target concentration (50.98%) and has superior accuracy compared to other related methods.

Fault Classification of Hydroelectric Generating Unit Based on Improved Evidence Theory

2014 ◽  
Vol 7 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Jiatang Cheng ◽  
Li Ai ◽  
Zhimei Duan ◽  
Yan Xiong
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fault Classification ◽  
Fusion Method ◽  
Inconsistent Result ◽  
High Conflict

Aiming at the problem of the conventional vibration fault diagnosis technology with inconsistent result of a hydroelectric generating unit, an information fusion method was proposed based on the improved evidence theory. In this algorithm, the original evidence was amended by the credibility factor, and then the synthesis rule of standard evidence theory was utilized to carry out information fusion. The results show that the proposed method can obtain any definitive conclusion even if there is high conflict evidence in the synthesis evidence process, and may avoid the divergent phenomenon when the consistent evidence is fused, and is suitable for the fault classification of hydroelectric generating unit.

Modeling and Simulation of Circulating Fluidized Bed Boiler Combustion System Based on Neural Network

2013 ◽  
Vol 706-708 ◽  
pp. 859-863
Author(s):  
Lin Lin Cui ◽  
Hua Lai ◽  
Xiao Qian Yu ◽  
Ming Jie Qi
Keyword(s):  
Neural Network ◽  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Paper Mill ◽  
Network Control ◽  
System Control ◽  
Combustion System ◽  
Circulating Fluidized Bed Boiler ◽  
Control Precision ◽  
Neural Network Algorithm

According to the multivariable coupling、 large time delay, non-linearity and time-varying and other difficulties of circulating fluidized bed boiler combustion system, a kind of control technology based on neural network to circulating fluidized bed boiler combustion system was presented. Actual parameter data of a paper mill in Kunming and neural network control principle were used in the establishment of a circulating fluidized bed boiler combustion system mathematical model and modified BP neural network algorithm training. Results of MATLAB simulation show that boiler combustion system control precision was effectively improved and good effects in production and application were got.

A novel information fusion method based on Dempster-Shafer evidence theory for conflict resolution

2011 ◽  
Vol 15 (3) ◽  
pp. 399-411 ◽  
Author(s):  
Jianping Yang ◽  
Hong-Zhong Huang ◽  
Qiang Miao ◽  
Rui Sun
Keyword(s):  
Conflict Resolution ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fusion Method
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