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A MLP solver for first and second order partial differential equations

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

A universal approximator, such as multilayer perceptron, is a tool that allows mapping of any multidimensional continuous function. The aim of this paper is to discuss a method of perceptron training that would result in its ability to map the functions constituting the solutions of partial differential equations of first and second order. The developed algorithm has been validated by means of equations whose analytical solutions are known.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2007 - 17th International Conference, Proceedings
PublisherSpringer Verlag
Pages789-797
Number of pages9
EditionPART 2
ISBN (Print)9783540746935
DOIs
Publication statusPublished - 2007
Event17th International Conference on Artificial Neural Networks, ICANN 2007 - Porto, Portugal
Duration: 9 Sept 2007 → 13 Sept 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume4669 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Artificial Neural Networks, ICANN 2007
Country/TerritoryPortugal
CityPorto
Period9/09/07 → 13/09/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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