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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

  • Czech description

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

    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

  • 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