EXTRA
发表于 2025-3-21 17:09:38
书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0315763<br><br> <br><br>书目名称Estimating Ore Grade Using Evolutionary Machine Learning Models读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0315763<br><br> <br><br>
Innocence
发表于 2025-3-21 21:53:53
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antidepressant
发表于 2025-3-22 02:43:44
Predicting Aluminum Oxide Grade,, MLP-NMR, MLP-SSA, MLP-PSO, MLP-GA, and MLP models were 10.12, 10.98, 11.12, 12.23, 14.45, and 15.56 at the testing level. The Nash Sutcliffe efficiencies (NSE) of the BMA, MLP-NMR, MLP-SSA, MLP-PSO, MLP-GA, and MLP models were 0.94, 0.92, 0.89, 0.86, 0.84, and 0.82 at the testing level.
Fibrillation
发表于 2025-3-22 05:43:54
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低位的人或事
发表于 2025-3-22 10:56:28
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Interdict
发表于 2025-3-22 16:58:12
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Interdict
发表于 2025-3-22 17:55:05
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Intellectual
发表于 2025-3-22 21:14:22
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摇曳的微光
发表于 2025-3-23 03:50:34
Estimating Iron Ore Grade,FA, GMDH-PSO, GMDH-GA, and GMDH were 4.55, 5.12, 5.54, 5.89, and 5.91. At the testing level, the GMDH-SSA decreased the MAE of the GMDH-SCA, GMDH-FFA, GMDH-PSO, GMDH-GA, and GMDH by 4.7, 14, 16, and 17%, respectively. The optimized GMDH models had a high potential for estimating iron ore grade.
seruting
发表于 2025-3-23 07:07:07
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