Login
Register
Reset Password
Publish & Distribute
Publishing Solutions
Distribution Solutions
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Blog
Contact
Search
EUR
USD
GBP
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Environmental and Climate Technologies
Volume 25 (2021): Issue 1 (January 2021)
Open Access
Office Building’s Occupancy Prediction Using Extreme Learning Machine Model with Different Optimization Algorithms
Violeta Motuzienė
Violeta Motuzienė
,
Jonas Bielskus
Jonas Bielskus
,
Vilūnė Lapinskienė
Vilūnė Lapinskienė
and
Genrika Rynkun
Genrika Rynkun
| Sep 20, 2021
Environmental and Climate Technologies
Volume 25 (2021): Issue 1 (January 2021)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Published Online:
Sep 20, 2021
Page range:
525 - 536
DOI:
https://doi.org/10.2478/rtuect-2021-0038
Keywords
CO (carbon dioxide)
,
Genetic Algorithm (GA)
,
office
,
Simulated Annealing (SA)
© 2021 Violeta Motuzienė et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Violeta Motuzienė
Vilnius Gediminas Technical University,
Vilnius, Lithuania
Jonas Bielskus
Vilnius Gediminas Technical University,
Vilnius, Lithuania
Vilūnė Lapinskienė
Vilnius Gediminas Technical University,
Vilnius, Lithuania
Genrika Rynkun
Vilnius Gediminas Technical University,
Vilnius, Lithuania