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Different Approaches for constant estimation in analytic programming

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517335" target="_blank" >RIV/70883521:28140/17:63517335 - isvavai.cz</a>

  • Alternative codes found

    RIV/70883521:28120/17:63517335

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Different Approaches for constant estimation in analytic programming

  • Original language description

    This research deals with different approaches for constant estimation in analytic programming (AP). AP is a tool for symbolic regression tasks which enables to synthesise an analytical solution based on the required behaviour of the system. Some tasks do not need any constant estimation - AP is used in its basic version without any constant estimation handling. Compared to this, cases like data approximation need constants (coefficients) which are essential for the process of precise solution synthesis. This paper offers another strategy to already known and used by the AP from the very beginning and approaches published recently in 2016. This paper compares these procedures and the discussion also includes nonlinear fitting and metaevolutionary approach. As the main evolutionary algorithm, a differential algorithm (de/rand/1/bin) for the main process of AP is used.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings - 31st European Conference on Modelling and Simulation, ECMS 2017

  • ISBN

    978-099324404-9

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    7

  • Pages from-to

    326-332

  • Publisher name

    European Council for Modelling and Simulation

  • Place of publication

    Madrid

  • Event location

    Budapešť

  • Event date

    May 23, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article