A hybrid Genetic Algorithm and Monte Carlo simulation approach to predict hourly energy consumption and generation by a cluster of Net Zero Energy Buildings
author
Garshasbi, Samira
Kurnitski, Jarek
Mohammadi, Yousef
statement of authorship
Samira Garshasbi, Jarek Kurnitski, Yousef Mohammadi
source
Applied energy
publisher
Elsevier
journal volume number month
vol. 179
year of publication
2016
pages
p. 626-637 : ill
url
https://doi.org/10.1016/j.apenergy.2016.07.033
subject term
taastuvenergia
Monte Carlo meetodid
geneetilised algoritmid
madalenergiamajad
koostöövõrgustikud
keyword
Monte Carlo simulation
genetic algorithm
renewable energy
ISSN
0306-2619
notes
Bibliogr.: 49 ref
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/28801
https://www.scopus.com/record/display.uri?eid=2-s2.0-84978785900&origin=inward&txGid=088d1083f11ee5517b904721614b8158
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=APPL%20ENERG&year=2023
https://www.webofscience.com/wos/woscc/full-record/WOS:000383291800051
category (general)
Engineering
Tehnika
Environmental science
Keskkonnateadus
Energy
Energia
category (sub)
Engineering. Building and construction
Tehnika. Ehitus ja ehitus
Environmental science. Management, monitoring, policy and law
Keskkonnateadus. Juhtimine, järelevalve, poliitika ja õigus
Engineering. Mechanical engineering
Tehnika. Masinaehitus
Energy. Renewable energy, sustainability and the environment
Energia. Taastuvenergia, jätkusuutlikkus ja keskkond
quartile
Q1
TalTech department
ehitiste projekteerimise instituut
language
inglise