An implementation of continuous genetic algorithm in parameter estimation of predator-prey model

Windarto, Windarto

doi:10.1063/1.4943352

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…In this section, we determine the parameter values of the mathematical model for the dynamics of shipping company competition in Surabaya. The parameter is estimated using the genetic algorithm since the exact solution of the model in equations ( 1)-( 3) could not be determined [10,11]. The data used to estimate the parameters is data on the number of container production or the number of containers by shipping companies every month from October 2018 ( 0) to September 2019 ( 11).…”

Section: -1mentioning

confidence: 99%

“…The parameter is estimated using the genetic algorithm since the exact solution of the model in equations ( 1)-( 3) could not be determined [10,11]. The data used to estimate the parameters is data on the number of container production or the number of containers by shipping companies every month from October 2018 ( 0) to September 2019 ( 11). The data are presented in Figure 1, Figure 2 and Figure 3, respectively.…”

Section: -1mentioning

confidence: 99%

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On mathematical model approach to competition dynamic of shipping companies in Surabaya

Windarto¹,

Fatmawati²,

Nuzulia³

2021

International Conference on Mathematics, Computational Sciences and Statistics 2020

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2020 has been a very challenging year due to Covid-19 pandemic, in which for the sake of safety and well-being of all participants, our initial plan to held ICoMCoS 2020 in Surabaya, Indonesia, has been converted to be fully delivered virtually. Nevertheless, while we may all be physically distant, we hope we can still connect intellectually.The theme of ICoMCoS 2020 is "Mathematics, Computational Sciences and Statistics for a Better Future". With increasing complexities of our world today, Mathematics, Computational Sciences and Statistics have become powerful tools to elucidate all the complexities as well as provide the solution. ICoMCoS 2020, in a more detail outfit, is designed to provide a multidisciplinary forum for promoting and fostering interactions between mathematics (Analysis and Geometry, Algebra and Combinatoric, Applied Mathematics), computational sciences (algorithm analysis, network security and cryptography, artificial intelligence and machine learning, knowledge discovery and data mining, machine translation, image processing), and statistics (statistical theory, statistics modeling, forecasting methods, multivariate methods, econometrics, biostatistics, actuarial sciences) as well as related methodologies in studying various phenomena in the area.We would like to say thanks to all authors who have submitted the paper to our proceedings. We also thank the scientific committee members and all of the reviewers for all supports during the conference and the preparation of the proceedings. As the scientific manuscripts of the conference, we provide the AIP Proceedings which contains the high-quality paper selected by a blind review process. We apologize to the authors if this process creates inconvenience.Last but not least, there have been enormous collective efforts being put to run ICoMCoS 2020, in one form or another, so, on behalf of the Program Committee, let me take this opportunity to express my high appreciation to all of those that have contributed.

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Section: -1mentioning

confidence: 99%

Section: -1mentioning

confidence: 99%

On mathematical model approach to competition dynamic of shipping companies in Surabaya

Windarto¹,

Fatmawati²,

Nuzulia³

2021

International Conference on Mathematics, Computational Sciences and Statistics 2020

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“…Sejarah awal tentang model prey-predator dapat dilihat pada Berryman dkk [10]. Beberapa penelitian yang menerapkan algoritma genetika dalam melakukan estimasi parameter untuk model prey-predator dapat dilihat di [11][12][13]. Di artikel ini akan dipelajari estimasi parameter dengan menggunakan data anjing hutan (coyote) dan kelinci besar (jackrabbit) yang masing-masing adalah predator dan prey di Southwest Prescott, Arizona [14].…”

Section: Introductionunclassified

Implementasi algoritma genetika dalam mengestimasi kepadatan populasi jackrabbit dan coyote

Savitri

Hidajati

Panigoro³

2022

Jambura J. Biomath.

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This article studies about the parameter estimation using genetic algorithm for a Lotka-Volterra prey-predator model. The secondary data consist of the density of jackrabbit as prey and coyote as predator in Southwest Presscott–Arizona are used. As results, the Mean Absolute Percentage Error (MAPE) are computed to compare the results of parameter estimation and the real data. We have shown that MAPE for jackrabbit and coyote respectively given by 7.75424% and 7.95283%. This results show that the parameter estimation with genetic algorithm using Lotka-Volterra model is passably. Furthermore, some numerical simulations are portrayed to show each population density for the next 100 years.

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“…This algorithm can be used to find solutions to problems with one or many variables, both continuous and discrete problems, and not only provide a single solution [12] . The genetic algorithm method has been previously applied to estimate parameters of the non-linear ordinary differential equations system model [9,[13][14][15] .…”

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confidence: 99%

A fractional model for the dynamics of competition between commercial and rural banks in Indonesia

Fatmawati

Khan

Azizah

et al. 2019

Chaos, Solitons & Fractals

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An implementation of continuous genetic algorithm in parameter estimation of predator-prey model

Cited by 7 publications

References 8 publications

On mathematical model approach to competition dynamic of shipping companies in Surabaya

On mathematical model approach to competition dynamic of shipping companies in Surabaya

Implementasi algoritma genetika dalam mengestimasi kepadatan populasi jackrabbit dan coyote

A fractional model for the dynamics of competition between commercial and rural banks in Indonesia

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