EFFCT 发表于 2025-3-21 18:02:23
书目名称Agents and Artificial Intelligence影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0151225<br><br> <br><br>书目名称Agents and Artificial Intelligence读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0151225<br><br> <br><br>CAMP 发表于 2025-3-21 21:54:48
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Shengyu Jian,Xin Chen,Jiaping Yanithms are trained with imbalanced data. Using an actual shill bidding dataset, we assess the performance of several hybrid models of CSL and SSC and then compare their misclassification error and accuracy rates statistically. The most efficient CSL+SSC model was able to detect 99% of fraudsters and with the lowest total cost.系列 发表于 2025-3-22 09:39:29
Meeko Kuwahara,Hiroki Takagi,Masaki Hayashidriven approach for the development of large numbers of schemas. Our empirical evaluation suggests that our developed system, which blends the advantages of Machine Learning and Natural Language Processing, is able to automatically develop Winograd schemas autonomously, or considerably help humans in the development task.sperse 发表于 2025-3-22 14:40:49
https://doi.org/10.1007/978-3-031-61147-6 for planning applications. Our experiments show that the technique is competitive with state-of-the-art domain-independent heuristic. We also introduce a theoretical framework to formally analyze behaviour of learned heuristics. We state and prove several theorems that establish bounds on the worst-case performance of learned heuristics.我没有命令 发表于 2025-3-22 19:55:40
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