Application of a fuzzy learning intervention approach to a purine metabolism pathway model

Nour Basha; Hazem N. Nounou; Mohamed N. Nounou

doi:10.1109/MECBME.2014.6783233

Application of a fuzzy learning intervention approach to a purine metabolism pathway model

Nour Basha, Hazem N. Nounou, Mohamed N. Nounou

Texas A&M University at Qatar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Adaptive fuzzy control is used here to enforce a concentration level of some metabolite of a biological system representing a purine metabolism pathway model to track a reference trajectory in the presence of uncertainties. In contrast to the direct fuzzy controller, the adaptive fuzzy controller is able to reduce the variance of both the system's response and the controller's output. In this paper, we will apply the adaptive fuzzy intervention strategy to the purine metabolism pathway model in the presence of output noise, which is the source of the model's uncertainties, and carry out a sensitivity analysis of the controller's behavior. The simulation will also be carried out using the direct fuzzy controllers, as described in [1], and the results will be compared and analyzed.

Original language	English
Title of host publication	2014 Middle East Conference on Biomedical Engineering, MECBME 2014
Publisher	IEEE Computer Society
Pages	171-174
Number of pages	4
ISBN (Print)	9781479947997
DOIs	https://doi.org/10.1109/MECBME.2014.6783233
Publication status	Published - 2014
Externally published	Yes
Event	2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014 - Doha, Qatar Duration: 17 Feb 2014 → 20 Feb 2014

Publication series

Name	Middle East Conference on Biomedical Engineering, MECBME
ISSN (Print)	2165-4247
ISSN (Electronic)	2165-4255

Conference

Conference	2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014
Country/Territory	Qatar
City	Doha
Period	17/02/14 → 20/02/14

Access to Document

10.1109/MECBME.2014.6783233

Cite this

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title = "Application of a fuzzy learning intervention approach to a purine metabolism pathway model",

abstract = "Adaptive fuzzy control is used here to enforce a concentration level of some metabolite of a biological system representing a purine metabolism pathway model to track a reference trajectory in the presence of uncertainties. In contrast to the direct fuzzy controller, the adaptive fuzzy controller is able to reduce the variance of both the system's response and the controller's output. In this paper, we will apply the adaptive fuzzy intervention strategy to the purine metabolism pathway model in the presence of output noise, which is the source of the model's uncertainties, and carry out a sensitivity analysis of the controller's behavior. The simulation will also be carried out using the direct fuzzy controllers, as described in [1], and the results will be compared and analyzed.",

author = "Nour Basha and Nounou, {Hazem N.} and Nounou, {Mohamed N.}",

year = "2014",

doi = "10.1109/MECBME.2014.6783233",

language = "English",

isbn = "9781479947997",

series = "Middle East Conference on Biomedical Engineering, MECBME",

publisher = "IEEE Computer Society",

pages = "171--174",

booktitle = "2014 Middle East Conference on Biomedical Engineering, MECBME 2014",

address = "United States",

note = "2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014 ; Conference date: 17-02-2014 Through 20-02-2014",

}

Basha, N, Nounou, HN & Nounou, MN 2014, Application of a fuzzy learning intervention approach to a purine metabolism pathway model. in 2014 Middle East Conference on Biomedical Engineering, MECBME 2014., 6783233, Middle East Conference on Biomedical Engineering, MECBME, IEEE Computer Society, pp. 171-174, 2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014, Doha, Qatar, 17/02/14. https://doi.org/10.1109/MECBME.2014.6783233

Application of a fuzzy learning intervention approach to a purine metabolism pathway model. / Basha, Nour; Nounou, Hazem N.; Nounou, Mohamed N.
2014 Middle East Conference on Biomedical Engineering, MECBME 2014. IEEE Computer Society, 2014. p. 171-174 6783233 (Middle East Conference on Biomedical Engineering, MECBME).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Application of a fuzzy learning intervention approach to a purine metabolism pathway model

AU - Basha, Nour

AU - Nounou, Hazem N.

AU - Nounou, Mohamed N.

PY - 2014

Y1 - 2014

N2 - Adaptive fuzzy control is used here to enforce a concentration level of some metabolite of a biological system representing a purine metabolism pathway model to track a reference trajectory in the presence of uncertainties. In contrast to the direct fuzzy controller, the adaptive fuzzy controller is able to reduce the variance of both the system's response and the controller's output. In this paper, we will apply the adaptive fuzzy intervention strategy to the purine metabolism pathway model in the presence of output noise, which is the source of the model's uncertainties, and carry out a sensitivity analysis of the controller's behavior. The simulation will also be carried out using the direct fuzzy controllers, as described in [1], and the results will be compared and analyzed.

AB - Adaptive fuzzy control is used here to enforce a concentration level of some metabolite of a biological system representing a purine metabolism pathway model to track a reference trajectory in the presence of uncertainties. In contrast to the direct fuzzy controller, the adaptive fuzzy controller is able to reduce the variance of both the system's response and the controller's output. In this paper, we will apply the adaptive fuzzy intervention strategy to the purine metabolism pathway model in the presence of output noise, which is the source of the model's uncertainties, and carry out a sensitivity analysis of the controller's behavior. The simulation will also be carried out using the direct fuzzy controllers, as described in [1], and the results will be compared and analyzed.

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DO - 10.1109/MECBME.2014.6783233

M3 - Conference contribution

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SN - 9781479947997

T3 - Middle East Conference on Biomedical Engineering, MECBME

SP - 171

EP - 174

BT - 2014 Middle East Conference on Biomedical Engineering, MECBME 2014

PB - IEEE Computer Society

T2 - 2014 2nd Middle East Conference on Biomedical Engineering, MECBME 2014

Y2 - 17 February 2014 through 20 February 2014

ER -

Application of a fuzzy learning intervention approach to a purine metabolism pathway model

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