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.
|Title of host publication||Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)|
|Editors||Javier Del Ser|
|Number of pages||7|
|Publication status||Published - 2017|
|Event||Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 - Bilbao, Spain|
Duration: 2017 Feb 22 → 2017 Feb 24
|Name||Advances in Intelligent Systems and Computing|
|Other||Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017|
|Period||17/2/22 → 17/2/24|
Bibliographical noteFunding 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.
© Springer Nature Singapore Pte Ltd. 2017.
- Approximate solution
- Artificial neural network
- Boundary value problems
- Differential equations
- Harmony search algorithm
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science(all)