Additive sequential evolutionary design of experiments

B. Balasko, J. Madar, J. Abonyi

Research output: Conference contribution

2 Citations (Scopus)

Abstract

Process models play important role in computer aided process engineering. Although the structure of these models are a priori known, model parameters should be estimated based on experiments. The accuracy of the estimated parameters largely depends on the information content of the experimental data presented to the parameter identification algorithm. Optimal experiment design (OED) can maximize the confidence on the model parameters. The paper proposes a new additive sequential evolutionary experiment design approach to maximize the amount of information content of experiments. The main idea is to use the identified models to design new experiments to gradually improve the model accuracy while keeping the collected information from previous experiments. This scheme requires an effective optimization algorithm, hence the main contribution of the paper is the incorporation of Evolutionary Strategy (ES) into a new iterative scheme of optimal experiment design (AS-OED). This paper illustrates the applicability of AS-OED for the design of feeding profile for a fed-batch biochemical reactor.

Original languageEnglish
Title of host publicationArtificial Intelligence and Soft Computing - ICAISC 2006 - 8th International Conference, Proceedings
PublisherSpringer Verlag
Pages324-333
Number of pages10
ISBN (Print)3540357483, 9783540357483
DOIs
Publication statusPublished - jan. 1 2006
Event8th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2006 - Zakopane, Poland
Duration: jún. 25 2006jún. 29 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4029 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2006
CountryPoland
CityZakopane
Period6/25/066/29/06

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Balasko, B., Madar, J., & Abonyi, J. (2006). Additive sequential evolutionary design of experiments. In Artificial Intelligence and Soft Computing - ICAISC 2006 - 8th International Conference, Proceedings (pp. 324-333). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4029 LNAI). Springer Verlag. https://doi.org/10.1007/11785231_35