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Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
- Source :
- Baghdad Science Journal, Vol 16, Iss 1 (2019)
- Publication Year :
- 2019
- Publisher :
- College of Science for Women, University of Baghdad, 2019.
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Abstract
- 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.
- Subjects :
- General Computer Science
Artificial neural network
General Mathematics
General Physics and Astronomy
General Chemistry
Fredholm integral equation
Agricultural and Biological Sciences (miscellaneous)
General Biochemistry, Genetics and Molecular Biology
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symbols
Applied mathematics
lcsh:Q
Feed Forward neural network, Levenberg – Marquardt (trainlm) training algorithm, Mixed Volterra - Fredholm integral equations
lcsh:Science
Mathematics
Subjects
Details
- Language :
- Arabic
- ISSN :
- 24117986 and 20788665
- Volume :
- 16
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Baghdad Science Journal
- Accession number :
- edsair.doi.dedup.....29bd306ce5b325f2bb949a44e355aab1