TY - JOUR
T1 - Evolutionary computational intelligence in solving a class of nonlinear Volterra–Fredholm integro-differential equations
AU - Kashkaria, Bothayna S.H.
AU - Syam, Muhammed I.
N1 - Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2017/2/1
Y1 - 2017/2/1
N2 - In this paper, a stochastic computational intelligence technique for solving a class of nonlinear Volterra–Fredholm integro-differential equations with mixed conditions is presented. The strength of feed forward artificial neural networks is used to accurately model the integro-equation. Comparisons with the exact solution and other numerical techniques are presented to show the efficiency of the proposed method. Theoretical and numerical results are presented. Analysis for the presented method is given.
AB - In this paper, a stochastic computational intelligence technique for solving a class of nonlinear Volterra–Fredholm integro-differential equations with mixed conditions is presented. The strength of feed forward artificial neural networks is used to accurately model the integro-equation. Comparisons with the exact solution and other numerical techniques are presented to show the efficiency of the proposed method. Theoretical and numerical results are presented. Analysis for the presented method is given.
KW - Artificial neural network
KW - Computational intelligence
KW - Volterra–Fredholm integro-differential equations
UR - http://www.scopus.com/inward/record.url?scp=84983405357&partnerID=8YFLogxK
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U2 - 10.1016/j.cam.2016.07.027
DO - 10.1016/j.cam.2016.07.027
M3 - Article
AN - SCOPUS:84983405357
SN - 0377-0427
VL - 311
SP - 314
EP - 323
JO - Journal of Computational and Applied Mathematics
JF - Journal of Computational and Applied Mathematics
ER -