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Study on the efficiency in the numerical integration of size-structured population models: Error and computational cost.

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Title: Study on the efficiency in the numerical integration of size-structured population models: Error and computational cost.
Authors: Angulo, O.1 oscar@mat.uva.es, López-Marcos, J.C.2 lopezmar@mac.uva.es, López-Marcos, M.A.2 malm@mac.uva.es
Source: Journal of Computational & Applied Mathematics. Jan2016, Vol. 291, p391-401. 11p.
Subjects: Error analysis in mathematics, Computational complexity, Finite difference method, Discretization methods, Mathematical models
Abstract: We describe a procedure which is useful to select an appropriate numerical method in a size-structured population model. We consider four different numerical methods based on finite difference schemes or characteristics curves integration. We compute an analytical approximation in terms of the discretization parameters for the theoretical error principal terms and the computational cost. Thus, we show the efficiency curve that allows to select the best relationship between the discretization parameters for each numerical method. Finally, we obtain the most efficient numerical method for each test. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computational & Applied Mathematics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 108941681
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Study on the efficiency in the numerical integration of size-structured population models: Error and computational cost.
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  Data: <searchLink fieldCode="AR" term="%22Angulo%2C+O%2E%22">Angulo, O.</searchLink><relatesTo>1</relatesTo><i> oscar@mat.uva.es</i><br /><searchLink fieldCode="AR" term="%22López-Marcos%2C+J%2EC%2E%22">López-Marcos, J.C.</searchLink><relatesTo>2</relatesTo><i> lopezmar@mac.uva.es</i><br /><searchLink fieldCode="AR" term="%22López-Marcos%2C+M%2EA%2E%22">López-Marcos, M.A.</searchLink><relatesTo>2</relatesTo><i> malm@mac.uva.es</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Computational+%26+Applied+Mathematics%22">Journal of Computational & Applied Mathematics</searchLink>. Jan2016, Vol. 291, p391-401. 11p.
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  Data: <searchLink fieldCode="DE" term="%22Error+analysis+in+mathematics%22">Error analysis in mathematics</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+complexity%22">Computational complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Finite+difference+method%22">Finite difference method</searchLink><br /><searchLink fieldCode="DE" term="%22Discretization+methods%22">Discretization methods</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink>
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  Label: Abstract
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  Data: We describe a procedure which is useful to select an appropriate numerical method in a size-structured population model. We consider four different numerical methods based on finite difference schemes or characteristics curves integration. We compute an analytical approximation in terms of the discretization parameters for the theoretical error principal terms and the computational cost. Thus, we show the efficiency curve that allows to select the best relationship between the discretization parameters for each numerical method. Finally, we obtain the most efficient numerical method for each test. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Computational & Applied Mathematics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.cam.2015.03.022
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        Text: English
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        PageCount: 11
        StartPage: 391
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      – SubjectFull: Error analysis in mathematics
        Type: general
      – SubjectFull: Computational complexity
        Type: general
      – SubjectFull: Finite difference method
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      – SubjectFull: Discretization methods
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      – SubjectFull: Mathematical models
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      – TitleFull: Study on the efficiency in the numerical integration of size-structured population models: Error and computational cost.
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              Text: Jan2016
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              Value: 291
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