Monsoon
发表于 2025-3-21 19:19:33
书目名称Artificial Intelligence影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0162066<br><br> <br><br>书目名称Artificial Intelligence读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0162066<br><br> <br><br>
思想上升
发表于 2025-3-21 20:41:26
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Ergots
发表于 2025-3-22 04:16:49
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可触知
发表于 2025-3-22 06:46:13
Some Determinants of Endogenous Growth search method is used in this problem. Here, the comparison has been made between PID controller tuned with different standard classical methods along with fuzzy PID (FPID) and proposed genetic algorithm based adaptive PID control (GAPID) technique. It has been found that better response is obtaine
有花
发表于 2025-3-22 10:27:06
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Anterior
发表于 2025-3-22 16:36:18
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暂时过来
发表于 2025-3-22 18:15:13
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省略
发表于 2025-3-22 23:35:20
Anomaly Detection in IoT Using Extended Isolation Forestators, including accuracy, precision, recall, and F1-Score, are used to validate the performance of our suggested system. We get an Accuracy Score of 93% and F1-Score of 96% through the experiment. In addition, the most important top 12 features have a more substantial impact on correct prediction f
进入
发表于 2025-3-23 03:15:06
A Novel Dimensionality Reduction Strategy Based on Linear Regression with a Fine-Pruned Decision Treon error. The effect of the complexity parameter on the number of nodes and the depth of the tree is discussed. The fine pruned tree is trained and validated on the CIC-IDS2017 dataset. The proposed work’s results are compared to the Random Forest(RF), Logistic Regression (LR) and Gradient boosting(
meditation
发表于 2025-3-23 08:28:10
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