Intimidate
发表于 2025-3-21 18:29:44
书目名称Artificial Intelligence and Soft Computing影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0162304<br><br> <br><br>书目名称Artificial Intelligence and Soft Computing读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0162304<br><br> <br><br>
忍受
发表于 2025-3-21 21:05:57
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颂扬本人
发表于 2025-3-22 04:09:14
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性别
发表于 2025-3-22 06:55:22
Incidental Neural Networks as Nomograms Generatorshe XIII Hilbert’s problem which was presented 1900 in the context of nomography, for the particular nomographic construction. The problem was solved by V. Arnold (a student of Andrey Kolomogorov) in 1957. For numeric data of unknown functional relation we developed the . as nomograms generators – the graphic calculating devices.
sphincter
发表于 2025-3-22 12:00:22
On Learning in a Time-Varying Environment by Using a Probabilistic Neural Network and the Recursivein time-varying environment. The general regression neural network is based on the orthogonal-type kernel functions. The appropriate algorithm is presented in a recursive form. Sufficient simulations confirm empirically the convergence of the algorithm.
Feature
发表于 2025-3-22 15:04:45
Fachenglisch für GesundheitsberufeThis paper presents the parallel architecture of the Recurrent Multi Layer Perceptron learning algorithm. The proposed solution is based on the high parallel three dimensional structure to speed up learning performance. Detailed parallel neural network structures are explicitly shown.
诱骗
发表于 2025-3-22 18:22:58
Fachenglisch für GesundheitsberufeSufficient conditions for uniform convergence of general regression neural networks, based on the orthogonal series-type kernel, are given. The convergence is guarantee even if variance of noise diverges to infinity. Simulation results are presented.
Consensus
发表于 2025-3-22 23:10:30
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mosque
发表于 2025-3-23 04:17:18
https://doi.org/10.1007/978-3-540-28534-2Sufficient conditions for strong convergence of recursive general regression neural networks are given assuming nonstationary noise. The orthogonal series-type kernel is applied. Simulation results show convergence even if variance of noise diverges to infinity.
摇曳
发表于 2025-3-23 05:39:00
Norma Huss,Sandra Schiller,Matthias SchmidtA problem of learning in non-stationary environment is solved by making use of order statistics in combination with the Parzen kernel-type regression neural network. Probabilistic properties of the algorithm are investigated and weak convergence is established. Experimental results are presented.