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dc.contributor.authorARIF, M. Ziaul
dc.contributor.authorANWAR, Zainul
dc.contributor.authorKAMSYAKAWUNI, Ahmad
dc.date.accessioned2020-11-18T06:50:04Z
dc.date.available2020-11-18T06:50:04Z
dc.date.issued2016-09-26
dc.identifier.urihttp://repository.unej.ac.id/handle/123456789/102060
dc.descriptionProceeding The 1st IBSC: Towards The Extended Use Of Basic Science For Enhancing Health, Environment, Energy And Biotechnologyen_US
dc.description.abstractNonlinear equation is a mathematical problem that is quite difficult to solve. Its analytic solution is not easily discovered. There are several methods used to solve nonlinear equations and the obtained results is in the form of approximation to the analytical solution. Most of the numerical method need appropriate initial value to perform the accuration of the method. However, it will diverge if the initial value is inappropriate. Therefore, we propose discovering the solutions of nonlinear equations by applying metaheuristic methods. In this paper, we present the virus Evolutionary Genetic Algorithm (VEGA) combined with Zero Crossing Method at an early stage to solve nonlinear equations. This study was conducted to test the performance and accuracy of the combined both of the method by providing some examples.en_US
dc.language.isoenen_US
dc.publisherUPT Penerbitan & Percetakan Universitas Jemberen_US
dc.subjectNonlinear equationen_US
dc.subjectVEGAen_US
dc.subjectZero crossingen_US
dc.titleA Zero Crossing-Virus Evolutionary Genetic Algorithm (VEGA) to Solve Nonlinear Equationsen_US
dc.typeArticleen_US
dc.identifier.kodeprodikodeprodi1810101#Matematika
dc.identifier.nidnNIDN0011018501
dc.identifier.nidnNIDN0029117202


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