The sample solution approach for determination of the optimal shape parameter in the Multiquadric function of the Kansa method
The Kansa method with the Multiquadric-radial basis function (MQ-RBF) is inherently meshfree and can achieve an exponential convergence rate if the optimal shape parameter is available. However, it is not an easy task to obtain the optimal shape parameter for complex problems whose analytical soluti...
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Veröffentlicht in: | Computers & mathematics with applications (1987) 2018-04, Vol.75 (8), p.2942-2954 |
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description | The Kansa method with the Multiquadric-radial basis function (MQ-RBF) is inherently meshfree and can achieve an exponential convergence rate if the optimal shape parameter is available. However, it is not an easy task to obtain the optimal shape parameter for complex problems whose analytical solution is often a priori unknown. This has long been a bottleneck for the MQ-Kansa method application to practical problems. In this paper, we present a novel sample solution approach (SSA) for achieving a reasonably good shape parameter of the MQ-RBF in the Kansa method for the solution of problems whose analytical solution is unknown. The basic assumption behind the SSA is that the optimal shape parameter is considered to be largely depended on the shape of computational domain, the type of the boundary conditions, the number and distribution of nodes, and the governing equation. In the procedure of the SSA, we set up a pseudo-problem as the sample solution whose solution is known. It is not difficult to obtain the optimal parameter of the MQ-RBF in the numerical solution of the pseudo-problem. The SSA suggests that the optimal shape parameter of the pseudo-problem can also achieve an approximately optimal accuracy in the solution of the original problem. Numerical examples and comparisons are provided to verify the proposed SSA in terms of accuracy and stability in solving homogeneous problems and non-homogeneous modified Helmholtz problems in several complex domains even using chaotic distribution of collocation points. |
doi_str_mv | 10.1016/j.camwa.2018.01.023 |
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However, it is not an easy task to obtain the optimal shape parameter for complex problems whose analytical solution is often a priori unknown. This has long been a bottleneck for the MQ-Kansa method application to practical problems. In this paper, we present a novel sample solution approach (SSA) for achieving a reasonably good shape parameter of the MQ-RBF in the Kansa method for the solution of problems whose analytical solution is unknown. The basic assumption behind the SSA is that the optimal shape parameter is considered to be largely depended on the shape of computational domain, the type of the boundary conditions, the number and distribution of nodes, and the governing equation. In the procedure of the SSA, we set up a pseudo-problem as the sample solution whose solution is known. It is not difficult to obtain the optimal parameter of the MQ-RBF in the numerical solution of the pseudo-problem. The SSA suggests that the optimal shape parameter of the pseudo-problem can also achieve an approximately optimal accuracy in the solution of the original problem. Numerical examples and comparisons are provided to verify the proposed SSA in terms of accuracy and stability in solving homogeneous problems and non-homogeneous modified Helmholtz problems in several complex domains even using chaotic distribution of collocation points.</description><identifier>ISSN: 0898-1221</identifier><identifier>EISSN: 1873-7668</identifier><identifier>DOI: 10.1016/j.camwa.2018.01.023</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Basis functions ; Kansa method ; Mathematical functions ; Mathematical models ; Meshless methods ; Multiquadric ; Parameter estimation ; Parameters ; Partial differential equations ; Radial basis function ; Sample solution approach ; Shape parameter</subject><ispartof>Computers & mathematics with applications (1987), 2018-04, Vol.75 (8), p.2942-2954</ispartof><rights>2018 Elsevier Ltd</rights><rights>Copyright Elsevier BV Apr 15, 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c376t-bad4086e8959bbbf9b4727d262aec746aea87fc9b62c6d45539454241914603d3</citedby><cites>FETCH-LOGICAL-c376t-bad4086e8959bbbf9b4727d262aec746aea87fc9b62c6d45539454241914603d3</cites><orcidid>0000-0001-5678-4949</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0898122118300397$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Chen, Wen</creatorcontrib><creatorcontrib>Hong, Yongxing</creatorcontrib><creatorcontrib>Lin, Ji</creatorcontrib><title>The sample solution approach for determination of the optimal shape parameter in the Multiquadric function of the Kansa method</title><title>Computers & mathematics with applications (1987)</title><description>The Kansa method with the Multiquadric-radial basis function (MQ-RBF) is inherently meshfree and can achieve an exponential convergence rate if the optimal shape parameter is available. However, it is not an easy task to obtain the optimal shape parameter for complex problems whose analytical solution is often a priori unknown. This has long been a bottleneck for the MQ-Kansa method application to practical problems. In this paper, we present a novel sample solution approach (SSA) for achieving a reasonably good shape parameter of the MQ-RBF in the Kansa method for the solution of problems whose analytical solution is unknown. The basic assumption behind the SSA is that the optimal shape parameter is considered to be largely depended on the shape of computational domain, the type of the boundary conditions, the number and distribution of nodes, and the governing equation. In the procedure of the SSA, we set up a pseudo-problem as the sample solution whose solution is known. It is not difficult to obtain the optimal parameter of the MQ-RBF in the numerical solution of the pseudo-problem. The SSA suggests that the optimal shape parameter of the pseudo-problem can also achieve an approximately optimal accuracy in the solution of the original problem. Numerical examples and comparisons are provided to verify the proposed SSA in terms of accuracy and stability in solving homogeneous problems and non-homogeneous modified Helmholtz problems in several complex domains even using chaotic distribution of collocation points.</description><subject>Basis functions</subject><subject>Kansa method</subject><subject>Mathematical functions</subject><subject>Mathematical models</subject><subject>Meshless methods</subject><subject>Multiquadric</subject><subject>Parameter estimation</subject><subject>Parameters</subject><subject>Partial differential equations</subject><subject>Radial basis function</subject><subject>Sample solution approach</subject><subject>Shape parameter</subject><issn>0898-1221</issn><issn>1873-7668</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kD9PwzAUxC0EEqXwCVgsMSfYjus4AwOq-CdALGW2XmxHdZXEqZ2AWPjsuC0DE9Mb7n73dIfQJSU5JVRcb3IN3SfkjFCZE5oTVhyhGZVlkZVCyGM0I7KSGWWMnqKzGDeEEF4wMkPfq7XFEbqhTce30-h8j2EYgge9xo0P2NjRhs71sJd8g8dE-GF0HbQ4rmGweIAA3c6GXb-XX6d2dNsJTHAaN1Ov_7LP0EfAyb_25hydNNBGe_F75-j9_m61fMxe3h6elrcvmS5KMWY1GE6ksLJaVHVdN1XNS1YaJhhYXXIBFmTZ6KoWTAvDF4ui4gvOOK0oF6QwxRxdHXJTse1k46g2fgp9eqkYKQWVIsUnV3Fw6eBjDLZRQ0g1w5eiRO2GVhu1H1rthlaEqjR0om4OlE0FPpwNKmpne22NC1aPynj3L_8DgeSJZA</recordid><startdate>20180415</startdate><enddate>20180415</enddate><creator>Chen, Wen</creator><creator>Hong, Yongxing</creator><creator>Lin, Ji</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-5678-4949</orcidid></search><sort><creationdate>20180415</creationdate><title>The sample solution approach for determination of the optimal shape parameter in the Multiquadric function of the Kansa method</title><author>Chen, Wen ; Hong, Yongxing ; Lin, Ji</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c376t-bad4086e8959bbbf9b4727d262aec746aea87fc9b62c6d45539454241914603d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Basis functions</topic><topic>Kansa method</topic><topic>Mathematical functions</topic><topic>Mathematical models</topic><topic>Meshless methods</topic><topic>Multiquadric</topic><topic>Parameter estimation</topic><topic>Parameters</topic><topic>Partial differential equations</topic><topic>Radial basis function</topic><topic>Sample solution approach</topic><topic>Shape parameter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Wen</creatorcontrib><creatorcontrib>Hong, Yongxing</creatorcontrib><creatorcontrib>Lin, Ji</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & mathematics with applications (1987)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Wen</au><au>Hong, Yongxing</au><au>Lin, Ji</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The sample solution approach for determination of the optimal shape parameter in the Multiquadric function of the Kansa method</atitle><jtitle>Computers & mathematics with applications (1987)</jtitle><date>2018-04-15</date><risdate>2018</risdate><volume>75</volume><issue>8</issue><spage>2942</spage><epage>2954</epage><pages>2942-2954</pages><issn>0898-1221</issn><eissn>1873-7668</eissn><abstract>The Kansa method with the Multiquadric-radial basis function (MQ-RBF) is inherently meshfree and can achieve an exponential convergence rate if the optimal shape parameter is available. However, it is not an easy task to obtain the optimal shape parameter for complex problems whose analytical solution is often a priori unknown. This has long been a bottleneck for the MQ-Kansa method application to practical problems. In this paper, we present a novel sample solution approach (SSA) for achieving a reasonably good shape parameter of the MQ-RBF in the Kansa method for the solution of problems whose analytical solution is unknown. The basic assumption behind the SSA is that the optimal shape parameter is considered to be largely depended on the shape of computational domain, the type of the boundary conditions, the number and distribution of nodes, and the governing equation. In the procedure of the SSA, we set up a pseudo-problem as the sample solution whose solution is known. It is not difficult to obtain the optimal parameter of the MQ-RBF in the numerical solution of the pseudo-problem. The SSA suggests that the optimal shape parameter of the pseudo-problem can also achieve an approximately optimal accuracy in the solution of the original problem. Numerical examples and comparisons are provided to verify the proposed SSA in terms of accuracy and stability in solving homogeneous problems and non-homogeneous modified Helmholtz problems in several complex domains even using chaotic distribution of collocation points.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.camwa.2018.01.023</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-5678-4949</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Basis functions Kansa method Mathematical functions Mathematical models Meshless methods Multiquadric Parameter estimation Parameters Partial differential equations Radial basis function Sample solution approach Shape parameter |
title | The sample solution approach for determination of the optimal shape parameter in the Multiquadric function of the Kansa method |
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