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Deep Neural Network-Based Impacts Analysis of Multimodal Factors on Heat Demand Prediction

  • Published:2020-09-01 Issue:3 Volume:6 Page:594-605
  • ISSN:2332-7790
  • Container-title:IEEE Transactions on Big Data
  • language:
  • Short-container-title:IEEE Trans. Big Data

Author:

Ma ZhanyuORCID,Xie JiyangORCID,Li Hailong,Sun Qie,Wallin Fredrik,Si ZhongweiORCID,Guo Jun

Funder

National Natural Science Foundation of China

Beijing Nova Program

Energimyndigheten and Energiforsk AB

Natural Science Foundation of Shandong Province

Fundamental Research Funds of Shandong University

BUPT Excellent PhD Students Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Information Systems

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3. Forecasting of residential unit’s heat demands: a comparison of machine learning techniques in a real-world case study;Energy Systems;2023-05-09

4. Short-Term Heat Demand Prediction Using Deep Learning for Decentralized Power-to-Heat Solutions;2023 IEEE PES GTD International Conference and Exposition (GTD);2023-05

5. Role of input features in developing data-driven models for building thermal demand forecast;Energy and Buildings;2022-12
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