HAND
发表于 2025-3-21 18:38:28
书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0884194<br><br> <br><br>书目名称Synergies of Soft Computing and Statistics for Intelligent Data Analysis读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0884194<br><br> <br><br>
CODA
发表于 2025-3-21 23:54:52
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morale
发表于 2025-3-22 02:07:45
2D Probability-Possibility Transformations-dimensional probability-possibility transformations of joint probability densities are considered, to build joint possibilities such that the marginals preserve the same information content as the marginals of the joint probability densities.
非实体
发表于 2025-3-22 06:10:21
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政府
发表于 2025-3-22 09:40:18
Cumulative Distribution Function Estimation with Fuzzy Data: Some Estimators and Further ProblemsIn this paper, we discuss two types of estimators for cumulative distribution function (CDF) based on fuzzy data: substituting estimators and nonparametric maximum likelihood (NPML) based estimators, both of them are extensions of empirical distribution functions (EDF) of real-valued (non-fuzzy) data. We also list some further problems.
中国纪念碑
发表于 2025-3-22 16:30:40
A Law of Large Numbers for Exchangeable Random Variables on Nonadditive MeasuresIn this paper, we use the relationship between set-valued random variables and capacity to prove a strong law of large numbers for exchangeable random variables with respect to nonadditive measures.
使更活跃
发表于 2025-3-22 21:05:57
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问到了烧瓶
发表于 2025-3-22 23:25:01
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Obstreperous
发表于 2025-3-23 02:58:11
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土产
发表于 2025-3-23 07:36:37
2194-5357 y, October 4-6,2012.Presents recent results illustrating new.In recent years there has been a growing interest to extend classical methods for data analysis..The aim is to allow a more flexible modeling of phenomena such as uncertainty, imprecision or ignorance..Such extensions of classical probabil