Simultaneous Prediction of Wind Speed and Direction by Evolutionary Fuzzy Rule Forest
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238690" target="_blank" >RIV/61989100:27240/17:10238690 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S187705091730786X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S187705091730786X?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.procs.2017.05.195" target="_blank" >10.1016/j.procs.2017.05.195</a>
Alternative languages
Result language
angličtina
Original language name
Simultaneous Prediction of Wind Speed and Direction by Evolutionary Fuzzy Rule Forest
Original language description
An accurate estimate of wind speed and direction is important for many application domains including weather prediction, smart grids, and e.g. traffic management. These two environmental variables depend on a number of factors and are linked together. Evolutionary fuzzy rules, based on fuzzy information retrieval and genetic programming, have been used to solve a variety of real-world regression and classification tasks. They were, however, limited by the ability to estimate only one variable by a single model. In this work, we introduce an extended version of this predictor that facilitates an artificial evolution of forests of fuzzy rules. In this way, multiple variables can be predicted by a single model that is able to comprehend complex relations between input and output variables. The usefulness of the proposed concept is demonstrated by the evolution of forests of fuzzy rules for simultaneous wind speed and direction prediction.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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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
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Procedia Computer Science. Volume 108
ISBN
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ISSN
1877-0509
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
295-304
Publisher name
Elsevier
Place of publication
Amsterdam
Event location
Curych
Event date
Jun 12, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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