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DC Field | Value | Language |
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dc.contributor.author | Eman Ali Hussian, Nahdh. S. M. Al_Saif | - |
dc.date.accessioned | 2022-10-24T19:02:31Z | - |
dc.date.available | 2022-10-24T19:02:31Z | - |
dc.date.issued | 2013 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/6229 | - |
dc.description.abstract | Recently, there has been an increasing interest in the study of singular and perturbed systems. In this paper design fast feed forward neural network to present a method to solve two dimensions singularly perturbed integro-differential and integral equations. Using a multi-layer having one hidden layer with 7 hidden units (neurons) and one linear output unit the sigmoid activation of each unit is radial basis function and Levenberg – Marquardt (trainlm) training algorithm. Finally the results of numerical experiments are compared with the exact solution in illustrative examples to confirm the accuracy and efficiency of the presented scheme | en_US |
dc.subject | singularly perturbed problems | en_US |
dc.subject | Volterra integral equations | en_US |
dc.subject | Volterra integro-differential equations | en_US |
dc.subject | feed forward neural network | en_US |
dc.subject | Levenbrg- Marquardt training. | en_US |
dc.title | Design feed forward neural network for solving two dimension singularly perturbed integrao-differential and integral equation | en_US |
dc.type | Article | en_US |
Appears in Collections: | قسم الرياضيات التطبيقية |
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File | Description | Size | Format | |
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Design feed forward neural network for solving two dimension singularly perturbed integrao-differential and integral equation.pdf | 394.46 kB | Adobe PDF | View/Open |
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