Nonlinear Analysis: Algorithm, Convergence, and Applications 2014

The article by H. Wang et al. considered the Cauchy problem for a fifth-order equation and proved its locally well-posed for the initial data in the Sobolev space [figure omitted; refer to PDF] with [figure omitted; refer to PDF] . [...]they also established the ill-posedness for the initial data in...

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Veröffentlicht in:Abstract and Applied Analysis Jg. 2014; S. 508 - 509-1553
Hauptverfasser: Song, Yisheng, Chen, Rudong, Li, Guoyin, Yang, Changsen, Yu, Gaohang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Hindawi Limiteds 01.01.2014
Hindawi Publishing Corporation
John Wiley & Sons, Inc
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ISSN:1085-3375, 1687-0409
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Abstract The article by H. Wang et al. considered the Cauchy problem for a fifth-order equation and proved its locally well-posed for the initial data in the Sobolev space [figure omitted; refer to PDF] with [figure omitted; refer to PDF] . [...]they also established the ill-posedness for the initial data in [figure omitted; refer to PDF] with [figure omitted; refer to PDF] . The article by C. Li et al. used the principal component analysis method to achieve dimensionality and correlation of input variables and obtained the three major factors affecting membrane fouling most obviously: MLSS, total resistance, and operating pressure, and applied genetic algorithm to optimize the initial weights and the threshold of BP neural network and established the membrane fouling prediction model based on GA-BP network.
AbstractList The article by H. Wang et al. considered the Cauchy problem for a fifth-order equation and proved its locally well-posed for the initial data in the Sobolev space [figure omitted; refer to PDF] with [figure omitted; refer to PDF] . [...]they also established the ill-posedness for the initial data in [figure omitted; refer to PDF] with [figure omitted; refer to PDF] . The article by C. Li et al. used the principal component analysis method to achieve dimensionality and correlation of input variables and obtained the three major factors affecting membrane fouling most obviously: MLSS, total resistance, and operating pressure, and applied genetic algorithm to optimize the initial weights and the threshold of BP neural network and established the membrane fouling prediction model based on GA-BP network.
Audience Academic
Author Yisheng Song
Changsen Yang
Rudong Chen
Guoyin Li
Gaohang Yu
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Copyright Copyright © 2014 Yisheng Song et al.
COPYRIGHT 2014 John Wiley & Sons, Inc.
COPYRIGHT 2015 John Wiley & Sons, Inc.
Copyright © 2014 Yisheng Song et al. Yisheng Song et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright 2014 Hindawi Publishing Corporation
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– notice: Copyright 2014 Hindawi Publishing Corporation
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StartPage 508
SubjectTerms Algorithms
Applied mathematics
Convergence (Mathematics)
Finite element analysis
Linear programming
Mathematical programming
Mathematical research
Nonlinear programming
Technology application
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