• شماره ركورد
    9766
  • پديد آورنده

    درسا عبدي

  • عنوان
    A novel approach for stock market prediction based on machine learning
  • مقطع تحصيلي
    كارشناسي
  • رشته تحصيلي
    علوم كامپيوتر
  • سال فارغ التحصيلي
    1404
  • استاد راهنما
    دكتر جواد وحيدي
  • استاد مشاور
    دكتر جواد وحيدي
  • دانشجوي وارد كننده اطلاعات

    درسا عبدي

  • تاريخ ورود اطلاعات
    1404/06/26
  • دانشكده
    رياضي و علوم كامپيوتر
  • عنوان به انگليسي
    رويكردي جديد براي پيش بيني بازار سهام بر اساس يادگيري ماشين
  • چكيده
    3-تعريف و اهميت موضوع price prediction is super challenging due to the nonlinearity, complexity, an‎d high noise present in financial time series. In the research, we are focusing on addressing this issue to enhance prediction performance in the complex stock market environment. To achieve this, we are proposing a novel integrated approach that utilizes Machine Learning techniques to simultaneously improve the fitting an‎d accuracy of stock price predictions. Additionally, to avoid the problem of overfitting an‎d further boost predictive performance, we are incorporating various ML algorithms for optimization. This study aims to leverage these advanced techniques to make more reliable an‎d accurate stock market predictions. price prediction is super challenging due to the nonlinearity, complexity, an‎d high noise present in financial time series. In the research, we are focusing on addressing this issue to enhance prediction performance in the complex stock market environment. To achieve this, we are proposing a novel integrated approach that utilizes Machine Learning techniques to simultaneously improve the fitting an‎d accuracy of stock price predictions. Additionally, to avoid the problem of overfitting an‎d further boost predictive performance, we are incorporating various ML algorithms for optimization. This study aims to leverage these advanced techniques to make more reliable an‎d accurate stock market predictions.
  • كليدواژه ها
    machine learning , lstm , hyperparameter