Machine Learning for Energy Load Prediction and its Interpretation

被引:0
作者
Charytanowicz, Malgorzata [1 ]
Olwert, Anna [2 ]
Radziszewska, Weronika [3 ]
Jarnicka, Jolanta [3 ]
Gajowniczek, Krzysztof [4 ]
Zabkowski, Tomasz [4 ]
Brozyna, Jacek [5 ]
Mentel, Grzegorz [5 ]
Matejko, Grzegorz [6 ]
机构
[1] Research Institute Pas, Center for Methods of Data Analysis Systems, Warsaw, Poland
[2] Research Institute Pas, Department of Computer Science Systems, Warsaw, Poland
[3] Research Institute Pas, Center for Computer Modelling Systems, Warsaw, Poland
[4] Warsaw University of Life Sciences, Institute of Information Technology, Warsaw, Poland
[5] Rzeszow University of Technology, Department of Quantitative Methods, Rzeszów, Poland
[6] Polskie Towarzystwo Cyfrowe, Lublin, Poland
来源
2022 IEEE 11th International Conference on Intelligent Systems, IS 2022 | 2022年
关键词
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I
11th IEEE International Conference on Intelligent Systems, IS 2022
中图分类号
学科分类号
摘要
Adaptive boosting - Additives - Electric load forecasting - Electric power plant loads - Machine learning - Regression analysis
引用
收藏
相关论文
共 50 条
  • [31] A Scoping Review of Energy Load Disaggregation
    Tolnai, Balázs András
    Ma, Zheng
    Jørgensen, Bo Nørregaard
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2023, 14116 LNAI : 209 - 221
  • [32] Peer to Peer Learning Platform Optimized With Machine Learning
    Anantha, Vikram
    arXiv, 2022,
  • [33] TraM: Enhancing User Sleep Prediction with Transformer-based Multivariate Time Series Modeling and Machine Learning Ensembles
    Kim, Jinjae
    Ma, Minjeong
    Choi, Eunjee
    Cho, Keunhee
    Lee, Changwoo
    arXiv,
  • [34] Prediction of Micro Vascular and Macro Vascular Complications in Type-2 Diabetic Patients using Machine Learning Techniques
    Vamsi, Bandi
    Al Bataineh, Ali
    Doppala, Bhanu Prakash
    International Journal of Advanced Computer Science and Applications, 2022, 13 (11): : 19 - 32
  • [35] Machine learning-based prediction of statically equivalent seismic forces in pin-supported cylindrical reticulated shells
    Department of Architecture and Civil Engineering, Toyohashi University of Technology, Toyohashi, Japan
    Int J Space Struct, 3 (198-210): : 198 - 210
  • [36] Deployment of Tile Using Machine Learning
    Gothwal, Pushpa
    Kumar, Ajay
    Vetriselvi, T.
    2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023, 2023,
  • [37] Tensor networks for unsupervised machine learning
    Liu, Jing
    Li, Sujie
    Zhang, Jiang
    Zhang, Pan
    PHYSICAL REVIEW E, 2023, 107 (01)
  • [38] Classification of Functions Using Machine Learning
    Lukac, Martin
    Yessenbayeva, Aigerim
    Lewis, Michael
    Podlaski, Krzysztof
    International Journal of Unconventional Computing, 2023, 18 (2-3) : 217 - 247
  • [39] Machine learning for optical quantum metrology
    Pezze, Luca
    ADVANCED PHOTONICS, 2023, 5 (02):
  • [40] Facial Expression Recognition with Machine Learning
    Chang, Jia Xiu
    Poo Lee, Chin
    Lim, Kian Ming
    Yan Lim, Jit
    2023 11th International Conference on Information and Communication Technology, ICoICT 2023, 2023, 2023-August : 125 - 130