Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network

Main Article Content

Al-Saif et al.

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.


                                 

Article Details

How to Cite
1.
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network. Baghdad Sci.J [Internet]. 2019 Mar. 11 [cited 2024 Mar. 28];16(1):0116. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3187
Section
article

How to Cite

1.
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network. Baghdad Sci.J [Internet]. 2019 Mar. 11 [cited 2024 Mar. 28];16(1):0116. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3187

Similar Articles

You may also start an advanced similarity search for this article.