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86e69ef24bb2ea3b30da · Forecasting Operation of a Chiller Plant Facility Using Data Driven Models

Forecasting Operation of a Chiller Plant Facility Using Data Driven Models

In recent years, data-driven models have enabled accurate prediction of chiller power consumption and chiller coefficient of performance (COP). This study evaluates the usage of time series Extreme Gradient Boosting (XGBoost) models to predict chiller

Официальный источник · 2024-07-23

Полные импортированные сведения карточки
{
  "title_en": "Forecasting Operation of a Chiller Plant Facility Using Data Driven Models",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2024-07-23",
  "date_original": "July 23, 2024",
  "url": "https://www.nist.gov/publications/forecasting-operation-chiller-plant-facility-using-data-driven-models",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Behzad Salimian Rizi, Afshin Faramarzi, Amanda Pertzborn , Mohammad Heidarinejad",
  "abstract_excerpt_en": "In recent years, data-driven models have enabled accurate prediction of chiller power consumption and chiller coefficient of performance (COP). This study evaluates the usage of time series Extreme Gradient Boosting (XGBoost) models to predict chiller",
  "id": "86e69ef24bb2ea3b30da",
  "sources": [
    "NIST Publications"
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    {
      "title_en": "Forecasting Operation of a Chiller Plant Facility Using Data Driven Models",
      "designation": "",
      "series": "",
      "status": "",
      "date": "2024-07-23",
      "date_original": "July 23, 2024",
      "url": "https://www.nist.gov/publications/forecasting-operation-chiller-plant-facility-using-data-driven-models",
      "source": "NIST Publications",
      "display_en": "",
      "authors_en": "Behzad Salimian Rizi, Afshin Faramarzi, Amanda Pertzborn , Mohammad Heidarinejad",
      "abstract_excerpt_en": "In recent years, data-driven models have enabled accurate prediction of chiller power consumption and chiller coefficient of performance (COP). This study evaluates the usage of time series Extreme Gradient Boosting (XGBoost) models to predict chiller"
    }
  ],
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}