衰退
发表于 2025-3-21 17:12:47
书目名称Belief Functions: Theory and Applications影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0183302<br><br> <br><br>书目名称Belief Functions: Theory and Applications读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0183302<br><br> <br><br>
filial
发表于 2025-3-21 21:19:12
Themenmotivation und Gang der Untersuchung,at can be summarized by three numbers characterizing the most plausible predicted value, variability around this value, and epistemic uncertainty. Experiments with real datasets demonstrate the very good performance of the method as compared to state-of-the-art evidential and statistical learning algorithms.
空洞
发表于 2025-3-22 01:04:55
Themenmotivation und Gang der Untersuchung,assifier, which can be scaled to 48 nodes (2688 cores) at a cluster named the Texas Advanced Computing Center Frontera, with several other parallel K-NN based algorithms over 4 large datasets. Our method is able to achieve state-of-the-art scaling efficiency and accuracy on the large datasets having more than 10 million samples.
narcissism
发表于 2025-3-22 05:12:21
Conference proceedings 2022 2022..The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine lear
engrossed
发表于 2025-3-22 08:58:23
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聚集
发表于 2025-3-22 14:24:07
An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbersat can be summarized by three numbers characterizing the most plausible predicted value, variability around this value, and epistemic uncertainty. Experiments with real datasets demonstrate the very good performance of the method as compared to state-of-the-art evidential and statistical learning algorithms.
售穴
发表于 2025-3-22 20:50:09
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自负的人
发表于 2025-3-22 23:45:20
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Gastric
发表于 2025-3-23 02:56:09
0302-9743 ubmissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more..978-3-031-17800-9978-3-031-17801-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
nugatory
发表于 2025-3-23 07:50:37
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