Dempster-Shafer evidence theory (D-S theory) provides a useful computational scheme for integrating uncertainty information from multiple sources in artificial intelligence systems. D-S evidence theory is a useful met...
详细信息
ISBN:
(纸本)9781424420957
Dempster-Shafer evidence theory (D-S theory) provides a useful computational scheme for integrating uncertainty information from multiple sources in artificial intelligence systems. D-S evidence theory is a useful method for dealing with uncertainty problems. Therefore, it has been successfully applied in data fusion and pattern recognition. However, it also has sonic shortcomings. The key problem to D-S reasoning is basicprobabilityassignment (BPA) function, which to a great extent limits its applications. To solve this problem, this paper presents three methods to constructing the BPA function. These methods are based on gray correlation analysis, fuzzy sets, and attribute measure respectively. Furthermore, experiments of recognizing the emitter purpose are selected to demonstrate these methods of determining the BPA function proposed. Experimental results show that the performance of these new methods is accurate and effective.
Dempster-Shafer evidence theory (D-S theory) provides a useful computational scheme for integrating uncertainty information from multiple sources in artificial intelligence systems. D-S evidence theory is a useful met...
详细信息
Dempster-Shafer evidence theory (D-S theory) provides a useful computational scheme for integrating uncertainty information from multiple sources in artificial intelligence systems. D-S evidence theory is a useful method for dealing with uncertainty problems. Therefore, it has been successfully applied in data fusion and pattern recognition. However, it also has some shortcomings. The key problem to D-S reasoning is basicprobabilityassignment (BPA) function, which to a great extent limits its applications. To solve this problem, this paper presents three methods to constructing the BPA function. These methods are based on gray correlation analysis, fuzzy sets, and attribute measure respectively. Furthermore, experiments of recognizing the emitter purpose are selected to demonstrate these methods of determining the BPA function proposed. Experimental results show that the performance of these new methods is accurate and effective.
In order to improve the image quality of multiphase flow process tomography system,a new fusion method of dual mode process tomography based on D-S evidence theory is *** CT system,due to the small angle of projection...
详细信息
ISBN:
(纸本)9781509046584
In order to improve the image quality of multiphase flow process tomography system,a new fusion method of dual mode process tomography based on D-S evidence theory is *** CT system,due to the small angle of projection,the reconstructed image edge prone to distortion,but Ray's hard field characteristics determine the image has a higher resolution;and ECT system,as the "soft field" characteristic of sensitive field,making the edges of the image with the actual situation reconstruction matches,but lower image *** on the analysis of the imaging mechanism and the aim of the fusion,the D-S evidence theory is applied to the CT/ECT image fusion,and the basicprobabilityassignment is indicated by the distance between the gray value and the cluster *** simulation results show that the proposed method can improve the quality of reconstructed image,and it is verified by the root mean square error.
Multi-sensor data fusion is a new technique developed in recent years, which is now widely applied to military and civilian areas. This paper mainly discusses the architecture and algorithm of multi-s
Multi-sensor data fusion is a new technique developed in recent years, which is now widely applied to military and civilian areas. This paper mainly discusses the architecture and algorithm of multi-s
In the battlefield environment, emitter information detected by multisensor takes on temporal redundancy. In order to solve emitter recognition problems in such practical reconnaissance environment, D
In the battlefield environment, emitter information detected by multisensor takes on temporal redundancy. In order to solve emitter recognition problems in such practical reconnaissance environment, D
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