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The application of fuzzy logistic equations in population growth with parameter estimation via minimization

This paper presents a numerical solution for the first order fuzzy logistic equations by extended Runge-Kutta fourth order method with estimated parameters. The parameters are estimated by minimization technique using conjugate gradient approach. Then, the fuzzy logistic model with the estimated par...

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Main Authors: Zulkefli, N. A. I., Su, H. Y., Maan, N.
Format: Article
Published: Penerbit UTM Press 2017
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/80944/
http://dx.doi.org/10.11113/mjfas.v13n2.564
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spelling my.utm.809442019-07-24T00:13:11Z http://eprints.utm.my/id/eprint/80944/ The application of fuzzy logistic equations in population growth with parameter estimation via minimization Zulkefli, N. A. I. Su, H. Y. Maan, N. QA Mathematics This paper presents a numerical solution for the first order fuzzy logistic equations by extended Runge-Kutta fourth order method with estimated parameters. The parameters are estimated by minimization technique using conjugate gradient approach. Then, the fuzzy logistic model with the estimated parameters is used to fit the population growth in Malaysia. Numerical example is given to show the efficiency of the proposed model. Penerbit UTM Press 2017 Article PeerReviewed Zulkefli, N. A. I. and Su, H. Y. and Maan, N. (2017) The application of fuzzy logistic equations in population growth with parameter estimation via minimization. Malaysian Journal of Fundamental and Applied Sciences, 13 (2). pp. 109-112. ISSN 2289-5981 http://dx.doi.org/10.11113/mjfas.v13n2.564 DOI:10.11113/mjfas.v13n2.564
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Zulkefli, N. A. I.
Su, H. Y.
Maan, N.
The application of fuzzy logistic equations in population growth with parameter estimation via minimization
description This paper presents a numerical solution for the first order fuzzy logistic equations by extended Runge-Kutta fourth order method with estimated parameters. The parameters are estimated by minimization technique using conjugate gradient approach. Then, the fuzzy logistic model with the estimated parameters is used to fit the population growth in Malaysia. Numerical example is given to show the efficiency of the proposed model.
format Article
author Zulkefli, N. A. I.
Su, H. Y.
Maan, N.
author_facet Zulkefli, N. A. I.
Su, H. Y.
Maan, N.
author_sort Zulkefli, N. A. I.
title The application of fuzzy logistic equations in population growth with parameter estimation via minimization
title_short The application of fuzzy logistic equations in population growth with parameter estimation via minimization
title_full The application of fuzzy logistic equations in population growth with parameter estimation via minimization
title_fullStr The application of fuzzy logistic equations in population growth with parameter estimation via minimization
title_full_unstemmed The application of fuzzy logistic equations in population growth with parameter estimation via minimization
title_sort application of fuzzy logistic equations in population growth with parameter estimation via minimization
publisher Penerbit UTM Press
publishDate 2017
url http://eprints.utm.my/id/eprint/80944/
http://dx.doi.org/10.11113/mjfas.v13n2.564
_version_ 1643658563161161728
score 13.211869

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