1 Ocak 2021 Dergi makalesi Açık Erişim

Ilhan, Fatih; Karaahmetoglu, Oguzhan; Balaban, Ismail; Kozat, Suleyman Serdar

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{
  "@context": "https://schema.org/", 
  "@id": 234290, 
  "@type": "ScholarlyArticle", 
  "creator": [
    {
      "@type": "Person", 
      "name": "Ilhan, Fatih"
    }, 
    {
      "@type": "Person", 
      "name": "Karaahmetoglu, Oguzhan"
    }, 
    {
      "@type": "Person", 
      "affiliation": "DataBoss AS, ODTU Teknokent, TR-06800 Ankara, Turkey", 
      "name": "Balaban, Ismail"
    }, 
    {
      "@type": "Person", 
      "name": "Kozat, Suleyman Serdar"
    }
  ], 
  "datePublished": "2021-01-01", 
  "description": "We investigate nonlinear regression for nonstationary sequential data. In most real-life applications such as business domains including finance, retail, energy, and economy, time series data exhibit nonstationarity due to the temporally varying dynamics of the underlying system. We introduce a novel recurrent neural network (RNN) architecture, which adaptively switches between internal regimes in a Markovian way to model the nonstationary nature of the given data. Our model, Markovian RNN employs a hidden Markov model (HMM) for regime transitions, where each regime controls hidden state transitions of the recurrent cell independently. We jointly optimize the whole network in an end-to-end fashion. We demonstrate the significant performance gains compared to conventional methods such as Markov Switching ARIMA, RNN variants and recent statistical and deep learning-based methods through an extensive set of experiments with synthetic and real-life datasets. We also interpret the inferred parameters and regime belief values to analyze the underlying dynamics of the given sequences.", 
  "headline": "Markovian RNN: An Adaptive Time Series Prediction Network With HMM-Based Switching for Nonstationary Environments", 
  "identifier": 234290, 
  "image": "https://aperta.ulakbim.gov.tr/static/img/logo/aperta_logo_with_icon.svg", 
  "license": "http://www.opendefinition.org/licenses/cc-by", 
  "name": "Markovian RNN: An Adaptive Time Series Prediction Network With HMM-Based Switching for Nonstationary Environments", 
  "url": "https://aperta.ulakbim.gov.tr/record/234290"
}