incompatible
发表于 2025-3-21 16:13:00
书目名称Advances in Neural Networks – ISNN 2012影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0149164<br><br> <br><br>书目名称Advances in Neural Networks – ISNN 2012读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0149164<br><br> <br><br>
COUCH
发表于 2025-3-21 21:12:04
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alcoholism
发表于 2025-3-22 02:42:21
https://doi.org/10.1007/978-3-642-31346-2algorithms; extreme learning machines; feature selection; fuzzy neural networks; machine learning; algori
Deadpan
发表于 2025-3-22 07:42:24
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DAUNT
发表于 2025-3-22 10:06:35
Jun Wang,Gary G. Yen,Marios M. PolycarpouUp to date results.State of the art research.Fast track conference proceedings
袭击
发表于 2025-3-22 16:23:46
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/149164.jpg
细胞学
发表于 2025-3-22 20:47:33
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ANIM
发表于 2025-3-22 21:26:41
M. Joseph Sirgy,Rhonda Phillips,Don R. Rahtz improve the efficacy of neural network training. However, those global algorithms suffer the curse of dimensionality. We propose a new approach that focuses on the topology of the solution space. Our method prunes the search space by using the Lipschitzian property of the criterion function. We hav
过分
发表于 2025-3-23 03:00:22
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achlorhydria
发表于 2025-3-23 06:47:37
https://doi.org/10.1007/978-94-007-0535-7based on mutual information and extreme learning machines is proposed in this paper. Simple mutual information based feature selection method is integrated with the fast learning kernel based extreme learning machines to obtain better modeling performance. In the method, optimal number of the featur