TY - GEN
T1 - Numerical solution of boundary value problems using artificial neural networks and harmony search
AU - Yadav, Neha
AU - Ngo, Thi Thuy
AU - Yadav, Anupam
AU - Kim, Joong Hoon
N1 - Funding Information:
This work was supported by a grant from the National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) under grant number NRF-2016R1A2A1A05005306, and a Brain Korea 21 (BK-21) fellowship from the Ministry of Education of Korea.
Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2017.
PY - 2017
Y1 - 2017
N2 - In this paper, we present an algorithm based on artificial neural networks (ANNs) and harmony search (HS) for the numerical solution of boundary value problems (BVPs), which evolves in most of the science and engineering applications. An approximate trial solution of the BVPs is constructed in terms of ANN in a way that it satisfies the desired boundary conditions of the differential equation (DE) a utomatically. Approximate satisfaction of the trial solution results in an unsupervised error, which is minimized by training ANN using the harmony search algorithm (HSA). A BVP modeling the flow of a stretching surface is considered here as a test problem to validate the accuracy, convergence and effectiveness of the proposed algorithm. The obtained results are compared with the available exact solution also to test the correctness of the algorithm.
AB - In this paper, we present an algorithm based on artificial neural networks (ANNs) and harmony search (HS) for the numerical solution of boundary value problems (BVPs), which evolves in most of the science and engineering applications. An approximate trial solution of the BVPs is constructed in terms of ANN in a way that it satisfies the desired boundary conditions of the differential equation (DE) a utomatically. Approximate satisfaction of the trial solution results in an unsupervised error, which is minimized by training ANN using the harmony search algorithm (HSA). A BVP modeling the flow of a stretching surface is considered here as a test problem to validate the accuracy, convergence and effectiveness of the proposed algorithm. The obtained results are compared with the available exact solution also to test the correctness of the algorithm.
KW - Approximate solution
KW - Artificial neural network
KW - Boundary value problems
KW - Differential equations
KW - Harmony search algorithm
UR - http://www.scopus.com/inward/record.url?scp=85012173215&partnerID=8YFLogxK
U2 - 10.1007/978-981-10-3728-3_12
DO - 10.1007/978-981-10-3728-3_12
M3 - Conference contribution
AN - SCOPUS:85012173215
SN - 9789811037276
T3 - Advances in Intelligent Systems and Computing
SP - 112
EP - 118
BT - Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)
A2 - Del Ser, Javier
PB - Springer Verlag
T2 - Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017
Y2 - 22 February 2017 through 24 February 2017
ER -