Academic Journal
View in EDS

Performance Analysis of SMDO Method with Benchmark Functions with Matlab Toolbox.

Bibliographic Details
Title: Performance Analysis of SMDO Method with Benchmark Functions with Matlab Toolbox.
Authors: AKPAMUKÇU, Mehmet, ATEŞ, Abdullah, ALAGÖZ, Barış Baykant
Source: Journal of the Institute of Science & Technology / Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi; Dec2020, Vol. 10 Issue 4, p2451-2460, 10p
Subject Terms: PARTICLE swarm optimization, MATHEMATICAL optimization, HEURISTIC
Reviews & Products: MATLAB (Computer software)
Abstract: SMDO method is a set and trial based optimization algorithm that is developed for online fine-tuning of controller parameters. SMDO method is implemented for several controller tuning applications. It can search parameter space with random backward and forward steps of each parameter. This property reduces risk of testing unstable control system configurations in controller design and thus makes the SMDO method more suitable for online parameter tuning of experimental systems. However, performance of SMDO has not been evaluated previously for benchmark functions in comparison with other well known heuristic optimization methods. This study aims to compare performances of Artificial Bee Colony (ABC), Cuckoo Search Optimization (CK), Particle Swarm Optimization (PSO) and Stochastic Multi-parameters Divergence Optimization (SMDO) methods for benchmark functions. Therefore, a benchmark tests program that is a user-friendly MATLAB GUI is introduced for user. This program can be downloaded from https://www.mathworks.com/matlabcentral/fileexchange/75043- smdo-method-with-benchmark-functions. [ABSTRACT FROM AUTHOR]
Copyright of Journal of the Institute of Science & Technology / Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi is the property of Igdir University, Institute of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
CustomLinks:
  – Url: https://resolver.ebsco.com/c/xy5jbn/result?sid=EBSCO:edb&genre=article&issn=21460574&ISBN=&volume=10&issue=4&date=20201201&spage=2451&pages=2451-2460&title=Journal of the Institute of Science & Technology / Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi&atitle=Performance%20Analysis%20of%20SMDO%20Method%20with%20Benchmark%20Functions%20with%20Matlab%20Toolbox.&aulast=AKPAMUK%C3%87U%2C%20Mehmet&id=DOI:10.21597/jist.722427
    Name: Full Text Finder (for New FTF UI) (s8985755)
    Category: fullText
    Text: Find It @ SCU Libraries
    MouseOverText: Find It @ SCU Libraries
Header DbId: edb
DbLabel: Complementary Index
An: 147667550
RelevancyScore: 915
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 915.372924804688
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Performance Analysis of SMDO Method with Benchmark Functions with Matlab Toolbox.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22AKPAMUKÇU%2C+Mehmet%22">AKPAMUKÇU, Mehmet</searchLink><br /><searchLink fieldCode="AR" term="%22ATEŞ%2C+Abdullah%22">ATEŞ, Abdullah</searchLink><br /><searchLink fieldCode="AR" term="%22ALAGÖZ%2C+Barış+Baykant%22">ALAGÖZ, Barış Baykant</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: Journal of the Institute of Science & Technology / Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi; Dec2020, Vol. 10 Issue 4, p2451-2460, 10p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22PARTICLE+swarm+optimization%22">PARTICLE swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%22MATHEMATICAL+optimization%22">MATHEMATICAL optimization</searchLink><br /><searchLink fieldCode="DE" term="%22HEURISTIC%22">HEURISTIC</searchLink>
– Name: SubjectProduct
  Label: Reviews & Products
  Group: Su
  Data: <searchLink fieldCode="PS" term="%22MATLAB+%28Computer+software%29%22">MATLAB (Computer software)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: SMDO method is a set and trial based optimization algorithm that is developed for online fine-tuning of controller parameters. SMDO method is implemented for several controller tuning applications. It can search parameter space with random backward and forward steps of each parameter. This property reduces risk of testing unstable control system configurations in controller design and thus makes the SMDO method more suitable for online parameter tuning of experimental systems. However, performance of SMDO has not been evaluated previously for benchmark functions in comparison with other well known heuristic optimization methods. This study aims to compare performances of Artificial Bee Colony (ABC), Cuckoo Search Optimization (CK), Particle Swarm Optimization (PSO) and Stochastic Multi-parameters Divergence Optimization (SMDO) methods for benchmark functions. Therefore, a benchmark tests program that is a user-friendly MATLAB GUI is introduced for user. This program can be downloaded from https://www.mathworks.com/matlabcentral/fileexchange/75043- smdo-method-with-benchmark-functions. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of the Institute of Science & Technology / Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi is the property of Igdir University, Institute of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://login.libproxy.scu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edb&AN=147667550
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.21597/jist.722427
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 2451
    Subjects:
      – SubjectFull: MATLAB (Computer software)
        Type: general
      – SubjectFull: PARTICLE swarm optimization
        Type: general
      – SubjectFull: MATHEMATICAL optimization
        Type: general
      – SubjectFull: HEURISTIC
        Type: general
    Titles:
      – TitleFull: Performance Analysis of SMDO Method with Benchmark Functions with Matlab Toolbox.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: AKPAMUKÇU, Mehmet
      – PersonEntity:
          Name:
            NameFull: ATEŞ, Abdullah
      – PersonEntity:
          Name:
            NameFull: ALAGÖZ, Barış Baykant
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2020
              Type: published
              Y: 2020
          Identifiers:
            – Type: issn-print
              Value: 21460574
          Numbering:
            – Type: volume
              Value: 10
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Journal of the Institute of Science & Technology / Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi
              Type: main
ResultId 1