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.

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.

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.

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.

Multi-Source Information Fusion Based on Data Driven

2010 ◽  
Vol 40-41 ◽  
pp. 121-126
Author(s):  
Xin Zhang ◽  
Li Yang ◽  
Yan Zhang
Keyword(s):  
Information Fusion ◽  
Rough Set Theory ◽  
Dimensional Space ◽  
System Modeling ◽  
Principal Component ◽  
Data Driven ◽  
Support Vector ◽  
Source Information ◽  
Knowledge Reduction ◽  
Lower Dimensional Space

Take data driven method as theoretical basis, study multi-source information fusion technology. Using online and off-line data of the fusion system, does not rely on system's mathematical model, has avoided question about system modeling by mechanism. Uses principal component analysis method, rough set theory, Support Vector Machine(SVM) and so on, three method fusions and supplementary, through information processing and feature extraction to system's data-in, catches the most important information to lower dimensional space, realizes knowledge reduction. From data level, characteristic level, decision-making three levels realize information fusion. The example indicated that reduced computational complexity, reduced information loss in the fusion process, and enhanced the fusion accuracy.

scholarly journals Latent Leakage Fault Identification and Diagnosis Based on Multi-Source Information Fusion Method for Key Pneumatic Units in Chinese Standard Electric Multiple Units (EMU) Braking System

2019 ◽  
Vol 9 (2) ◽  
pp. 300
Author(s):  
Jianyong Zuo ◽  
Jingxian Ding ◽  
Furen Feng
Keyword(s):  
Support Vector Machine ◽  
Information Fusion ◽  
Small Sample ◽  
Support Vector ◽  
Ratio Test ◽  
Fusion Method ◽  
Source Information ◽  
Braking System ◽  
Chinese Standard ◽  
Multiple Units

To identify and diagnose the latent leakage faults of key pneumatic units in the Chinese standard Electric Multiple Units (EMU) braking system, a multi-source information fusion method based on Kalman filtering, sequential probability ratio test (SPRT), and support vector machine (SVM) is proposed. The relay valve is taken as an example for research. Firstly, Kalman's state estimation function is used to obtain the innovation sequence, and the innovation sequence is input into the SPRT model to help recognize latent leakage faults of the relay valve. Using this method, the problem of the incomplete training set of the traditional SPRT method due to the change of the braking level and the vehicle load is solved. Secondly, the eight time-domain parameters of the relay valve input and the output pressure signal are extracted as fault characteristics, and then input to the support vector machine to realize the internal and external leakage fault diagnosis of the relay valve, which provides a reference for maintenance. Finally, this method is verified by the fault simulation data by quickly identifying latent leakage faults and diagnosing the internal and external leakage at a fault recognition rate of 100% by SVM under small sample conditions.

Study on Fault Diagnosis of Ship Power System Based on Multi-Source Information Fusion Technology

2014 ◽  
Vol 644-650 ◽  
pp. 3726-3729 ◽  
Author(s):  
Lei Liu ◽  
Xiu Qiang Li
Keyword(s):  
Fault Diagnosis ◽  
Power System ◽  
Information Fusion ◽  
Evidence Theory ◽  
Theory Method ◽  
Fusion Technology ◽  
Source Information ◽  
Ship Power System ◽  
The Impact ◽  
Electrical Data

This paper firstly establishes a mathematical model of ship power system, and then analyzes the characteristics and common faults of ship power system. D-S evidence theory method is used on research of common faults of the ship power system, to enhance the pertinence of fault diagnosis. By using multi-source information fusion diagnosis, the need for quantities of electrical data is reduced, and, it can effectively reduce the impact of protection or switch malfunction on the fault diagnosis of ship power system and thus improve the accuracy of diagnosis.

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