Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear...
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| Language: | English |
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University of Baghdad, College of Science for Women
2019-03-01
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| Series: | مجلة بغداد للعلوم |
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| Online Access: | http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3187 |
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| author | Al-Saif et al. |
| author_facet | Al-Saif et al. |
| author_sort | Al-Saif et al. |
| collection | DOAJ |
| description | In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method. |
| format | Article |
| id | doaj-art-705fc073b4654d3b9cc6f2c025f1dc30 |
| institution | Kabale University |
| issn | 2078-8665 2411-7986 |
| language | English |
| publishDate | 2019-03-01 |
| publisher | University of Baghdad, College of Science for Women |
| record_format | Article |
| series | مجلة بغداد للعلوم |
| spelling | doaj-art-705fc073b4654d3b9cc6f2c025f1dc302025-08-20T03:33:54ZengUniversity of Baghdad, College of Science for Womenمجلة بغداد للعلوم2078-86652411-79862019-03-0116110.21123/bsj.16.1.01163187Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural NetworkAl-Saif et al.In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3187Feed Forward neural network, Levenberg – Marquardt (trainlm) training algorithm, Mixed Volterra - Fredholm integral equations |
| spellingShingle | Al-Saif et al. Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network مجلة بغداد للعلوم Feed Forward neural network, Levenberg – Marquardt (trainlm) training algorithm, Mixed Volterra - Fredholm integral equations |
| title | Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network |
| title_full | Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network |
| title_fullStr | Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network |
| title_full_unstemmed | Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network |
| title_short | Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network |
| title_sort | solving mixed volterra fredholm integral equation mvfie by designing neural network |
| topic | Feed Forward neural network, Levenberg – Marquardt (trainlm) training algorithm, Mixed Volterra - Fredholm integral equations |
| url | http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3187 |
| work_keys_str_mv | AT alsaifetal solvingmixedvolterrafredholmintegralequationmvfiebydesigningneuralnetwork |