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1)  BPAF
基本可信度赋值函数
2)  basic probability assignment function
基本概率赋值函数
1.
Aiming at the problem of basic probability assignment function conformation to Dempster-Shafer evidence reasoning, this paper presents a new conformation method based on fuzzy cluster analysis, then applies it to simulation experiments of radar target recognition, and compares it to the gray correlation method.
针对Dempster-Shafer(D-S)证据推理中基本概率赋值函数的构造问题,基于模糊聚类分析给出了一种新的构建方法。
3)  general basic belief assignment(GBBA)
广义基本信度赋值
1.
During the multi-source information fusion with Dezert-Smarandache theory(D-SmT),the problem of the subjectivity exists in getting the mathematical model of general basic belief assignment(GBBA).
在运用Dezert-Smarandache理论(D-SmT)进行多源信息融合过程中,传感器的广义基本信度赋值(GBBA)数学模型的获取较困难,且存在主观性的问题。
4)  valuation density function
赋值密度函数
1.
Taking the valuation lattice to be the unit interval ,this paper introduces the valuation density function and defines the probability truth degree.
取赋值格为[0,1],引入赋值密度函数,定义了命题公式的概率真度,并讨论几种赋值密度函数的形态,得到一些概率真度推理规则。
2.
The valuation density function of formulas in the continuous value propositional logic system is proposed on the idea of conditional probability.
基于条件概率的思想,在连续值命题逻辑系统中引入赋值密度函数概念,给出了公式的概率真度、数学期望、条件概率真度的定义,并得到了一些概率真度的推理规则。
3.
The valuation density function of formulas in continuous value propositional logic system is obtained based on the idea of conditional probability.
基于条件概率的思想,在Gdel连续值命题逻辑系统中引入赋值密度函数概念,给出了公式的概率真度、条件概率真度的定义,定义了公式间的相似度和伪距离并给出了相关的性质。
5)  reliability function
可信度函数
1.
In this paper, the major works are as follows:In this paper, a method for text categorization based on the fusion of multiple classifiers was presented, reliability function was introduction to select the text that hard to give determine by the main classifier, for these texts, multiple classifiers were used to give the determine which category the unlabeled documents belong to by voting.
通过引入可信度函数,选择出主分类器较难判决的文本,通过辅助分类器,对单一主分类器不易判决的文本通过多分类器投票方式进行判决。
2.
It was to evaluate the experimental result of single classifier using the reliability function,to classify the documents that were hard to be classified by voting.
通过引入可信度函数对单分类器效果进行评价,适时采用辅助分类器对较难分类的文档进行分类投票判决。
6)  belief density function
可信度密度函数
补充资料:可信度
可信度:指一项测试对其所测度的东西具有前后一致性。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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