Local Polynomial Regression Solution for Partial Differential Equations with Initial and Boundary Values
Local polynomial regression (LPR) is applied to solve the partial differential equations (PDEs). Usually, the solutions of the problems are separation of variables and eigenfunction expansion methods, so we are rarely able to find analytical solutions. Consequently, we must try to find numerical sol...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2012/201678 |
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| Summary: | Local polynomial regression (LPR) is applied to solve the partial differential equations (PDEs). Usually, the solutions of the problems are
separation of variables and eigenfunction expansion methods, so we are rarely
able to find analytical solutions. Consequently, we must try to find numerical
solutions. In this paper, two test problems are considered for the numerical
illustration of the method. Comparisons are made between the exact solutions and the results of the LPR. The results of applying this theory to the
PDEs reveal that LPR method possesses very high accuracy, adaptability,
and efficiency; more importantly, numerical illustrations indicate that the new
method is much more efficient than B-splines and AGE methods derived for
the same purpose. |
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| ISSN: | 1026-0226 1607-887X |