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Importance of Feature Selection for Recurrent Neural Network Based Forecasting of Building Thermal Comfort

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00219453" target="_blank" >RIV/68407700:21230/14:00219453 - isvavai.cz</a>

  • Result on the web

    <a href="http://link.springer.com/chapter/10.1007%2F978-3-319-11298-5_2#page-1" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-11298-5_2#page-1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-11298-5_2" target="_blank" >10.1007/978-3-319-11298-5_2</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Importance of Feature Selection for Recurrent Neural Network Based Forecasting of Building Thermal Comfort

  • Original language description

    The paper demonstrates the importance of feature selection for recurrent neural network applied to problem of one hour ahead forecasting of thermal comfort for office building heated by gas. Although the accuracy of the forecasting is similar for both the feed-forward and the recurrent network, the removal of features leads to accuracy reduction much earlier for the feed-forward network. The recurrent network can perform well even with less than 50% of features. This brings significant benefits in scenarios, where the neural network is used as a blackbox model of thermal comfort, which is called by an optimizer that minimizes the deviance from a target value. The reduction of input dimensionality can lead to reduction of costs related to measurement equipment, data transfer and also computational demands of optimization.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GP13-21696P" target="_blank" >GP13-21696P: Feature selection for temporal context aware models of multivariate time series</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Adaptive and Intelligent Systems - LNAI 8779

  • ISBN

    978-3-319-11297-8

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    11-19

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Bournemouth

  • Event date

    Sep 8, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000346932400002