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evidence combination     
相关语句
  证据合成
     To improve the reliability of small target recognition, a method called multi sensor information fusion identification based on D S theory of evidence combination is proposed.
     为了提高低信噪比弱小目标识别的可信度 ,提出了一种基于D S证据合成理论的多传感器信息融合识别方法。
短句来源
     The evidence combination problem in Dempster- Shafer's theory is studied in the paper.
     本文研究Dempster-Shafer理论中的证据合成问题。
短句来源
     In order to improve the reliability of small target recognition under strong clutter, a method called IR small target recognition based on multi sensors spatio temporal information fusion was proposed. And the D S theory of evidence combination was used in the simulation calculation of information fusion of image from multiple IR sensors.
     为了提高强干扰条件下的红外弱小目标识别的可靠性 ,提出了一种基于多传感器时间 空间信息融合的红外小目标识别方法 ,并采用D S证据合成理论对来自多个红外双波段成像传感器的实际图像信息进行了仿真融合计算 .
短句来源
     EVIDENCE COMBINATION AND DECISION BASED ON DS EVIDENCE THEORY AND EVIDENCE CLASSIFICATION
     基于证据分类的DS证据合成及判决方法
短句来源
     Research and Improvement of Conflict Evidence Combination Method
     冲突证据合成方法研究及改进
短句来源
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  证据组合
     Evidence Combination Methods in D-S Evidence Theory
     D-S证据理论中的证据组合
短句来源
     Multisensor target recognition based on the weighted evidence combination
     基于加权证据组合的多传感器目标识别
短句来源
     RECOGNITION OF COMMUNICATION SIGNALS BASED ON EVIDENCE COMBINATION
     基于证据组合的通信信号调制类型的分类识别
短句来源
     In this paper, the evidence combination principles of D-S evidence theory are repre-sented in detail firstly.
     详细阐述了D-S证据理论的相关理论和证据组合原理;
短句来源
     A few concepts of D-S evidence theory and D-S evidence combination rule and decision methods are presented and the program of D-S evidence combination rule on Basic Probability Assignment Function (BPAF) is described.
     本文在简要介绍D -S证据组合理论框架基础上 ,阐述了基于D -S证据组合理论的信息融合一般步骤及决策层判决方法 ;
短句来源
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  证据组合理论
     A few concepts of D-S evidence theory and D-S evidence combination rule and decision methods are presented and the program of D-S evidence combination rule on Basic Probability Assignment Function (BPAF) is described.
     本文在简要介绍D -S证据组合理论框架基础上 ,阐述了基于D -S证据组合理论的信息融合一般步骤及决策层判决方法 ;
短句来源
     Two fusion methods is proposed under different situations are proposed with evidence combination theory. One is the combination algorithm of results output by multi-classifier.
     用证据组合理论融合多源信息时,提出了在两种不同情况的融合算法:其一,多分类器输出结果的组合算法,取出同一对象的不同分类特征组,对所有的分类特征组分别设计出具有不同分类能力的神经网络分类器,并用遗传算法训练神经网络;
短句来源
     First, a few concepts of D - S evidence theory, D -S evidence combination rule and decisions method are briefly introduced, and the programs of D - S evidence combination rule based on BPAF is described.
     简要介绍了D-S证据组合理论框架,阐述了基于BPAF判决的决策层目标属性融合策略、步骤;
短句来源
     The knowledge fusing equation was induced following D-S evidence combination rule.
     针对企业失败预警问题,推导了基于D-S证据组合理论的知识融合公式;
短句来源
  证据结合
     The Recognition of Target and Decoy Using D S Evidence Combination Method
     D—S证据结合方法用于目标和诱饵的识别
短句来源
     Application of Evidence Combination to Fault Diagnosis of Electric Power Equipment
     证据结合在电力设备故障诊断中的应用
短句来源
     This paper deals with the recognition of target and decoy. D S evidence combination method is applied to recognize target and decoy.
     本文以目标和诱饵的识别为背景、详细叙述了D-S证据结合方法的原理、融合模型和识别结果;
短句来源
     The basic principles of the application of evidence combination to electric power equipment and the steps of fault diagnosis are presented。 Finally,the fault diagnosis of transformer insulation is carried out based on the calculation of Basic Probability Assignment(BPA).
     首先介绍了证据结合在电力设备故障诊断中的基本原理 ,然后给出了电力设备故障诊断的基本步骤 ,最后以变压器的绝缘诊断为例 ,进行了计算和诊断
短句来源

 

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  evidence combination
To effectively integrate multi-features, we also investigated the following evidence combination techniques-Certainty Factor, Dempster Shafer Theory, Compound Probability, and Linear Combination.
      
In the proposed scheme textual and colour features are combined using the Dempster-Shafer theory of evidence combination.
      
This robust method can resolve the conflicts resulting from either the mutual dependency among evidences or the structural dependency in an inference network due to the evidence combination order.
      
Currently there are many ad-hoc evidence combination formulae as well as those based on specific methodologies such as the Bayesian, likelihood, etc.
      
The system is being designed to compare and combine methodologies ranging from an implementation of the doctor's decision making protocols to classical statistical, machine learning and evidence combination schemes.
      
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