Natural Behavior Learning for Developing an Innovation of Computational Intelligence Applied to a Technical Quadratic Problem

DOI

10.2991/icovet-18.2019.26How to use a DOI?

Keywords

Economic dispatch, salmon behaviors, power commitment, technical problem, innovation development

Abstract

Recently, many algorithms have been presented for new approaches based on natural inspirations as introduced in this paper is explored from the migrating Salmon mechanism. This approach is Artificial Salmon Tracking Algorithm (ASTA) which is tested on a standard system model for carrying out a dynamic economic dispatch. In these studies, ASTA is also used to optimize the system and to get an optimal portion of the balanced combination. The results show that the solution is produced dynamically to make the optimal operation for 24 hours. The system model can be balanced based on the quadratic model while ASTA has been demonstrated clearly to search for optimal solutions.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Arif Nur Afandi
AU  - Anik Nur Handayani
AU  - Dyah Lestari
AU  - I Made Wirawan
AU  - F. C. W. Afandi F. C. W. Afandi
AU  - M. R. S. Afandi M. R. S. Afandi
PY  - 2019/01
DA  - 2019/01
TI  - Natural Behavior Learning for Developing an Innovation of Computational Intelligence Applied to a Technical Quadratic Problem
BT  - Proceedings of the 2nd International Conference on Vocational Education and Training (ICOVET 2018)
PB  - Atlantis Press
SP  - 106
EP  - 110
SN  - 2352-5398
UR  - https://doi.org/10.2991/icovet-18.2019.26
DO  - 10.2991/icovet-18.2019.26
ID  - NurAfandi2019/01
ER  -