Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 26th European Conference on Modelling and Simulation, ECMS 2012 |
| Subtitle of host publication | Shaping reality through simulation |
| Pages | 332-338 |
| Publication status | Published - 2012 |
| Event | 26th European Conference on Modelling and Simulation, ECMS 2012 - Koblenz, Germany Duration: 29 May 2012 → 1 Jun 2012 |
Publication series
| Name | Proceedings - 26th European Conference on Modelling and Simulation, ECMS 2012 |
|---|
Abstract
Process data-based system identification is one great challenge in technical process modelling and simulation. In this paper we continue our former work presented in [1], [3] and concentrate on the analysis and evaluation of both the data preprocessing and different search metrics used in the multi-agent-based optimization algorithm. This analysis helps to review and benchmark the impact on different preprocessing steps as well as the influence of the selected search metrics. Based on this evaluation we are able to verify the correct and target-oriented identification procedure.
Keywords
- Agent-based evolutionary computation, Memetic optimization algorithms, System identification
ASJC Scopus subject areas
- Mathematics(all)
- Modelling and Simulation
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Proceedings - 26th European Conference on Modelling and Simulation, ECMS 2012: Shaping reality through simulation. 2012. p. 332-338 (Proceedings - 26th European Conference on Modelling and Simulation, ECMS 2012).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Analysis of different search metrics used in multi-agent-based identification environment
AU - Bohlmann, Sebastian
AU - Klauke, Arne
AU - Klinger, Volkhard
AU - Szczerbicka, Helena
PY - 2012
Y1 - 2012
N2 - Process data-based system identification is one great challenge in technical process modelling and simulation. In this paper we continue our former work presented in [1], [3] and concentrate on the analysis and evaluation of both the data preprocessing and different search metrics used in the multi-agent-based optimization algorithm. This analysis helps to review and benchmark the impact on different preprocessing steps as well as the influence of the selected search metrics. Based on this evaluation we are able to verify the correct and target-oriented identification procedure.
AB - Process data-based system identification is one great challenge in technical process modelling and simulation. In this paper we continue our former work presented in [1], [3] and concentrate on the analysis and evaluation of both the data preprocessing and different search metrics used in the multi-agent-based optimization algorithm. This analysis helps to review and benchmark the impact on different preprocessing steps as well as the influence of the selected search metrics. Based on this evaluation we are able to verify the correct and target-oriented identification procedure.
KW - Agent-based evolutionary computation
KW - Memetic optimization algorithms
KW - System identification
UR - http://www.scopus.com/inward/record.url?scp=85088755239&partnerID=8YFLogxK
U2 - 10.7148/2012-0332-0338
DO - 10.7148/2012-0332-0338
M3 - Conference contribution
AN - SCOPUS:85088755239
SN - 9780956494443
T3 - Proceedings - 26th European Conference on Modelling and Simulation, ECMS 2012
SP - 332
EP - 338
BT - Proceedings - 26th European Conference on Modelling and Simulation, ECMS 2012
T2 - 26th European Conference on Modelling and Simulation, ECMS 2012
Y2 - 29 May 2012 through 1 June 2012
ER -