Wind Speed Prediction with Genetic Algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241737" target="_blank" >RIV/61989100:27240/18:10241737 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-65636-6_29" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-65636-6_29</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-65636-6_29" target="_blank" >10.1007/978-3-319-65636-6_29</a>
Alternative languages
Result language
angličtina
Original language name
Wind Speed Prediction with Genetic Algorithm
Original language description
Nowadays trends pay attention to used renewable energy sources, e.g. wind - wind energy or sun irradiance - solar energy, as a source of electrical power. This kind of energy sources are very unstable and inconstancy (nonstationary) over the time. The proper and accurate wind speed or sun irradiance prediction is necessary to control the power grid. This paper presents short time wind prediction algorithm with genetic column subset selection problem. It uses multiple weather data sources, genetics algorithm for features selection, and the prediction is done by a neural network. The genetic algorithm chooses the most important features for the prediction algorithm.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GJ16-25694Y" target="_blank" >GJ16-25694Y: Multi-paradigm data mining algorithms based on information retrieval, fuzzy, and bio-inspired methods</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes on Data Engineering and Communications Technologies. Volume 8
ISBN
978-3-319-65635-9
ISSN
2367-4512
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
326-335
Publisher name
Springer
Place of publication
Cham
Event location
Toronto
Event date
Aug 24, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000434865700029