一再 发表于 2025-3-21 19:32:29
书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0427078<br><br> <br><br>书目名称Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0427078<br><br> <br><br>Alienated 发表于 2025-3-21 20:38:01
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A. Ramachandra Rao,En-Ching Hsuion. Alas, this comes with a great increase in computational time, encumbering the optimization process. With the growing adoption rate for smart wells in oil field development projects, these optimizations are indispensable as to justify the investment on the technology and maximize financial returPsychogenic 发表于 2025-3-22 08:26:10
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A. Ramachandra Rao,En-Ching Hsu approaches such as “Tangent Learning Vector Quantization" and “Tangent Distance Kernel for Support Vector Machines" for classification of data. These models assume that there are class invariant manifolds that can be locally approximated by an affine space of similar dimensions. However, in practicCRP743 发表于 2025-3-23 02:17:05
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A. Ramachandra Rao,En-Ching HsuThe method is especially useful for localizing objects in images. Here, we extend the method to the task of joint localization of several objects in a 2D-image by means of combining several centroids. The novel approach, i.e. joint optimization of several centroids and a subsequent optimization of t