Natural Behavior Learning for Developing an Innovation of Computational Intelligence Applied to a Technical Quadratic Problem
Authors
Arif Nur Afandi, Anik Nur Handayani, Dyah Lestari, I Made Wirawan, F. C. W. Afandi F. C. W. Afandi, M. R. S. Afandi M. R. S. Afandi
Corresponding Author
Arif Nur Afandi
Available Online January 2019.
- 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/).
Cite this article
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 -