A Novel Parameter Optimization Metaheuristic: Human Habitation Behavior Based Optimization

Parameters have great impact on the performance of an optimization algorithm. This paper concerns parameter tuning for metaheuristics which are stochastic optimization algorithms. A novel, fast, and very simple population-based metaheuristic namely Human Habitation Behavior-Based optimization (HHBO)...

Full description

Saved in:
Bibliographic Details
Published in2022 5th International Conference on Contemporary Computing and Informatics (IC3I) pp. 921 - 924
Main Authors Jain, Divya, Arya, Mithlesh, Malik, Varun, Singh, S Vikram
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.12.2022
Subjects
Feed-forward neural networks
Metaheuristics
Parameter tuning
Weight and bias optimization
Online AccessGet full text
DOI10.1109/IC3I56241.2022.10072699

Cover

Abstract Parameters have great impact on the performance of an optimization algorithm. This paper concerns parameter tuning for metaheuristics which are stochastic optimization algorithms. A novel, fast, and very simple population-based metaheuristic namely Human Habitation Behavior-Based optimization (HHBO) is proposed in order to tune parameters of the metaheuristics used for the weight and bias optimization problem in feed-forward neural networks. The proposed algorithm is compared with other state-of-art algorithms, and results and analysis are presented. The results show the merits of HHBO for parameter tuning in comparison of other state-of-art algorithms.
AbstractList Parameters have great impact on the performance of an optimization algorithm. This paper concerns parameter tuning for metaheuristics which are stochastic optimization algorithms. A novel, fast, and very simple population-based metaheuristic namely Human Habitation Behavior-Based optimization (HHBO) is proposed in order to tune parameters of the metaheuristics used for the weight and bias optimization problem in feed-forward neural networks. The proposed algorithm is compared with other state-of-art algorithms, and results and analysis are presented. The results show the merits of HHBO for parameter tuning in comparison of other state-of-art algorithms.
Author Malik, Varun
Singh, S Vikram
Jain, Divya
Arya, Mithlesh
Author_xml – sequence: 1
  givenname: Divya
  surname: Jain
  fullname: Jain, Divya
  email: divyabairathijain@yahoo.co.in
  organization: Poornima College of Engineering,Computer Engineering Department,Jaipur,India
– sequence: 2
  givenname: Mithlesh
  surname: Arya
  fullname: Arya, Mithlesh
  email: mithlesh.arya@poornima.org
  organization: Poornima College of Engineering,Computer Engineering Department,Jaipur,India
– sequence: 3
  givenname: Varun
  surname: Malik
  fullname: Malik, Varun
  email: varun.malik@chitkara.edu.in
  organization: Chitkara University,Chitkara University Institute of Engineering and Technology,Punjab,India
– sequence: 4
  givenname: S Vikram
  surname: Singh
  fullname: Singh, S Vikram
  email: svikram@gn.amity.edu
  organization: Amity University,Noida,India
BookMark eNpVj8FOwzAQRI0EByj9AyT8AwlrO7Gz3NoImkqFcoALl2qTLKqlJqkctxJ8PUiFA6c5jN7ozZU474eehbhVkCoFeLcszTK3OlOpBq1TBeC0RTwTU3RYmBwMFtq6S_E-k8_DkXfyhQJ1HDnI9T76zn9R9EMvnzjSlg_Bj9E397I6dNTLimofT_2ct3T0Q5BzGrn9x16Liw_ajTz9zYl4e3x4LatktV4sy9kq8UphTBiBDaiG2BCgYcwLlyntCv4xrrUxVLcus1YTGEAowFJeE0KWQ8Mts5mIm9OuZ-bNPviOwufm77L5Bly3URM
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/IC3I56241.2022.10072699
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9798350398267
EndPage 924
ExternalDocumentID 10072699
Genre orig-research
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i119t-e90e301cae3a093e958741278e269b233abd74662a03090806a5ba90450cedee3
IEDL.DBID RIE
IngestDate Wed Aug 27 02:52:59 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i119t-e90e301cae3a093e958741278e269b233abd74662a03090806a5ba90450cedee3
PageCount 4
ParticipantIDs ieee_primary_10072699
PublicationCentury 2000
PublicationDate 2022-Dec.-14
PublicationDateYYYYMMDD 2022-12-14
PublicationDate_xml – month: 12
  year: 2022
  text: 2022-Dec.-14
  day: 14
PublicationDecade 2020
PublicationTitle 2022 5th International Conference on Contemporary Computing and Informatics (IC3I)
PublicationTitleAbbrev IC3I
PublicationYear 2022
Publisher IEEE
Publisher_xml – name: IEEE
Score 2.044978
Snippet Parameters have great impact on the performance of an optimization algorithm. This paper concerns parameter tuning for metaheuristics which are stochastic...
SourceID ieee
SourceType Publisher
StartPage 921
SubjectTerms Feed-forward neural networks
Metaheuristics
Parameter tuning
Weight and bias optimization
Title A Novel Parameter Optimization Metaheuristic: Human Habitation Behavior Based Optimization
URI https://ieeexplore.ieee.org/document/10072699
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3PS8MwFA5uJ08qTvxNDl7bNUmbNd50ODZhcwcHw8vIj1cUdZPRevCv9yXtFAXBWyktTd8j-b68974XQi4KFeSXNnKpwQ1Kqk2kIAOc8cLZQvOcWR_vGE_kcJbezrN5I1YPWhgACMVnEPvLkMt3K1v5UFnXZ_S5VKpFWr1c1mKtpmaLJao76osRwnnqt32cx5unf5ybEmBjsEMmmw_W1SLPcVWa2H786sX47xHtks63Qo9Ov7Bnj2zBcp88XNHJ6h1e6FT7kiu0GL3DFeG1kVrSMZT6Eaq6N_MlDfF7OtSmadNNm16Ja3qN0OZ-vNshs8HNfX8YNWcnRE-MqTIClQDOXatB6EQJUFmO3IH3csDhGi6ENq6XSsm1z7EgbZQ6M1ohwUssOABxQNrL1RIOCc0csiRXpAL_CZ2Ja4ArCmZY4qRFOiCPSMcbZvFWt8dYbGxy_Mf9E7Lt_eNrQlh6StrluoIzRPbSnAePfgLRhaTm
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV09T8MwELWgDDABoohvPLAmTWLHrdmgAqXQhg6tVLFU_rgIBLSoShj49ZyTFFQkJLYoShTnTvZ7vrt3JuQik6X80niWa9ygcKU9CTHgjGfWZCrqhMbFOwapSMb8bhJParF6qYUBgLL4DHx3Weby7dwULlTWchn9SEi5TjZiznlcybXqqq0wkK1el_UQ0Lnb-EWRv3x-5eSUEjhut0m6_GRVL_LiF7n2zeevboz_HtMOaf5o9OjwG312yRrM9sjjFU3nH_BKh8oVXaHN6AOuCW-12JIOIFdPUFTdmS9pGcGnidJ1o25ad0tc0GsEN7vybpOMb29G3cSrT0_wnsNQ5h7IAHD2GgVMBZKBjDvIHqJ2B3C4OmJMadvmQkTKZVmQOAoVayWR4gUGLADbJ43ZfAYHhMYWeZLNOMN_QnfiKmCzLNRhYIVBQiAOSdMZZvpeNciYLm1y9Mf9c7KZjAb9ab-X3h-TLecrVyES8hPSyBcFnCLO5_qs9O4Xo2WoMw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2022+5th+International+Conference+on+Contemporary+Computing+and+Informatics+%28IC3I%29&rft.atitle=A+Novel+Parameter+Optimization+Metaheuristic%3A+Human+Habitation+Behavior+Based+Optimization&rft.au=Jain%2C+Divya&rft.au=Arya%2C+Mithlesh&rft.au=Malik%2C+Varun&rft.au=Singh%2C+S+Vikram&rft.date=2022-12-14&rft.pub=IEEE&rft.spage=921&rft.epage=924&rft_id=info:doi/10.1109%2FIC3I56241.2022.10072699&rft.externalDocID=10072699