Overcoming detection rate bottlenecks in new QoS violation with combining HMM and information fusion theory

2015 ◽  
pp. 1759-1763
Author(s):  
Mei Yang ◽  
Jian Kang ◽  
Junyao Zhang
Keyword(s):  
Information Fusion ◽  
Detection Rate ◽  
Fusion Theory

scholarly journals Advances in Multi-Sensor Information Fusion: Theory and Applications 2017

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1162 ◽  
Author(s):  
Xue-Bo Jin ◽  
Shuli Sun ◽  
Hong Wei ◽  
Feng-Bao Yang
Keyword(s):  
Information Fusion ◽  
Sensor Information ◽  
Fusion Theory

The Research on Fault Diagnosis of Civil Aircraft Information Fusion Based on the Evidence Theory

2014 ◽  
Vol 983 ◽  
pp. 392-395
Author(s):  
Xue Peng
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Similarity Coefficient ◽  
Maintenance Cost ◽  
Civil Aircraft ◽  
Fusion Theory ◽  
Improved Methods

In this paper, information fusion theory based on the evidence theory is used in the fault diagnosis field of civil aircraft. Considering the conflict resulted from information fusion in some certain conditions, two improved methods, including Similarity Coefficient and Full Factor are put forward to solve the conflict problems. In a nutshell, the methods are pretty effective and reliable, and the maintenance cost of airlines can be reduced obviously.

Urban Rail Transit Financial Subsidy Decision Based on Information Fusion

2013 ◽  
Vol 361-363 ◽  
pp. 1954-1957
Author(s):  
Hong Yan Liang ◽  
Jian Jun Wang
Keyword(s):  
Information Fusion ◽  
Decision Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Subsidy Policy ◽  
Urban Rail ◽  
Fusion Theory ◽  
Internet Of Things Technology ◽  
The Internet Of Things ◽  
Financial Subsidy

The Internet of things technology provides a new model for reference for information fusion. Based on information fusion theory and methods for relative basic data fusion, established the urban rail transit financial subsidy decision model by using the marginal cost method, which assist to decide the urban rail transit finance subsidy policy.

Research on Acoustic Monitoring for Boiler Tube Leakage Based on Information Fusion Theory

2013 ◽  
Vol 760-762 ◽  
pp. 886-890
Author(s):  
Peng Tong ◽  
Chun Jing Geng
Keyword(s):  
Neural Network ◽  
Information Fusion ◽  
Initial Phase ◽  
Evidence Theory ◽  
Acoustic Monitoring ◽  
Boiler Tube ◽  
Monitoring Method ◽  
Fusion Theory

The problem of how to detect and diagnose the tube leakage and blast through the methods of acoustics and information fusion is dealt with in this paper with the purpose of detecting the accident more accurately at its initial phase. Firstly, the acoustic monitoring method is employed since it is contactless, and then the weak leakage is detected, analyzed and diagnosed through such methods as the PCA, neural network and D-S evidence theory. Secondly, the simulation is conducted, which testifies that the diagnosis effect can be improved greatly by this way.

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.

Research on Reliability Assessment for the Armored Equipment Based on Multi-Source Information Fusion

2013 ◽  
Vol 760-762 ◽  
pp. 2091-2094
Author(s):  
Jian Du ◽  
Bao Jun Fei ◽  
Ying Liu ◽  
Guo Zheng Yao
Keyword(s):  
Field Test ◽  
Test Data ◽  
Information Fusion ◽  
Reliability Assessment ◽  
Small Sample ◽  
Test Results ◽  
Fuzzy Information ◽  
Source Information ◽  
Sample Test ◽  
Fusion Theory

In order to solve the problem of reliability evaluation for armored equipment, used Bayes fusion theory, combined with minimal amounts of reliability information on the field test, the paper fusioned reliability information of the same model for armored equipment, and completed the reliability assessment for a certain type of armored equipment. The test results show that the technology of multi-source information fusion can effectively solve the fusion problem of the prior fuzzy information and small sample test data, improve the accuracy of the reliability assessment, prove the feasibility and effectiveness for the multi-source information fusion in the armored equipment assessment.

Multimodal Information Fusion of Audiovisual Emotion Recognition Using Novel Information Theoretic Tools

2013 ◽  
Vol 4 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Zhibing Xie ◽  
Ling Guan
Keyword(s):  
Emotion Recognition ◽  
Information Fusion ◽  
Feature Space ◽  
Information Theoretic ◽  
Second Order Statistics ◽  
Entropy Estimation ◽  
Multimodal Information Fusion ◽  
Multimodal Information ◽  
Improved Performance ◽  
Fusion Theory

This paper aims at providing general theoretical analysis for the issue of multimodal information fusion and implementing novel information theoretic tools in multimedia application. The most essential issues for information fusion include feature transformation and reduction of feature dimensionality. Most previous solutions are largely based on the second order statistics, which is only optimal for Gaussian-like distribution, while in this paper we describe kernel entropy component analysis (KECA) which utilizes descriptor of information entropy and achieves improved performance by entropy estimation. The authors present a new solution based on the integration of information fusion theory and information theoretic tools in this paper. The proposed method has been applied to audiovisual emotion recognition. Information fusion has been implemented for audio and video channels at feature level and decision level. Experimental results demonstrate that the proposed algorithm achieves improved performance in comparison with the existing methods, especially when the dimension of feature space is substantially reduced.

Sign in / Sign up

Export Citation Format

Share Document