Function approximation of seawater density using genetic algorithm

  • Abdulrahman Ahmed Bobakr Baqais*
  • , Moataz Ahmed
  • , Mostafa H. Sharqawy
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Function Approximation is a popular engineering method used in system identification or equation optimization. Artificial Intelligence (AI) techniques have been used extensively to spot the best curves that match the real behavior of the system due to the wide spectrum of the search space. Genetic algorithm is well-known for its fast convergence and ability to find an optimal structure of the solution. In this paper, we propose using a genetic algorithm method as a function approximator to get a correlation for seawater density. We will use a polynomial form of the approximation. After implementing the algorithm, the results from the produced function are compared with the real data used in the algorithm.

Original languageEnglish
Title of host publicationProceedings of the World Congress on Engineering 2013, WCE 2013
Pages820-825
Number of pages6
StatePublished - 2013

Publication series

NameLecture Notes in Engineering and Computer Science
Volume2 LNECS
ISSN (Print)2078-0958

Keywords

  • Correlation
  • Function approximation
  • Genetic algorithm
  • System identification

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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