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SCALABLE ACTIVATION FUNCTION EMPLOYMENT IN PHYSICS INFORMED HIGHER ORDER NEURAL NETWORKS FOR INITIAL VALUE PROBLEM APPROXIMATION

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F23%3A00370807" target="_blank" >RIV/68407700:21220/23:00370807 - isvavai.cz</a>

  • Result on the web

    <a href="https://isimconference.eu/" target="_blank" >https://isimconference.eu/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    SCALABLE ACTIVATION FUNCTION EMPLOYMENT IN PHYSICS INFORMED HIGHER ORDER NEURAL NETWORKS FOR INITIAL VALUE PROBLEM APPROXIMATION

  • Original language description

    There are many physical phenomena in the engineering applications, which are governed by ordinary differential equations. In the practice these problems are approximated using classical numerical methods. Present contribution deals with an alternative approximation method – higher order neural networks and furthermore, employment of the scalable activation function which can accelerate speed of the convergence is discussed. Basic ideas of the methods are introduced and designed architectures are tested on initial value problem. A comparison of the results quality between three neural network architectures is performed. Improvement in the speed of the convergence has been reached.

  • 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

    <a href="/en/project/EF16_019%2F0000826" target="_blank" >EF16_019/0000826: Center of Advanced Aerospace Technology</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    BOOK OF ABSTRACTS ISIM&ISWIM

  • ISBN

  • ISSN

    2821-8779

  • e-ISSN

    2821-8779

  • Number of pages

    2

  • Pages from-to

    88-89

  • Publisher name

    1 Decembrie 1918 University

  • Place of publication

    Alba Iulia

  • Event location

    Bucharest

  • Event date

    Jun 28, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article