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A Neural Network for Monitoring and Characterization of Buildings with Environmental Quality Management, Part 1: Verification under Steady State Conditions

Author

Listed:
  • Marek Dudzik

    (Department of Traction and Traffic Control, Faculty of Electrical and Computer Engineering, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, Poland)

  • Anna Romanska-Zapala

    (Department of Automation and Information Technology, Faculty of Electrical and Computer Engineering, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, Poland)

  • Mark Bomberg

    (Mechanical and Aeronautical Engineering, Clarkson University, Potsdam, New York, NY 13699, USA)

Abstract

Introducing integrated, automatic control to buildings operating with the environmental quality management (EQM) system, we found that existing energy models are not suitable for use in integrated control systems as they poorly represent the real time, interacting, and transient effects that occur under field conditions. We needed another high-precision estimator for energy efficiency and indoor environment and to this end we examined artificial neural networks (ANNs). This paper presents a road map for design and evaluation of ANN-based estimators of the given performance aspect in a complex interacting environment. It demonstrates that in creating a precise representation of a mathematical relationship one must evaluate the stability and fitness under randomly changing initial conditions. It also shows that ANN systems designed in this manner may have a high precision in characterizing the response of the building exposed to the variable outdoor climatic conditions. The absolute value of the relative errors ( M a x A R E ) being less than 1.4% for each stage of the ANN development proves that our objective of monitoring and EQM characterization can be reached.

Suggested Citation

  • Marek Dudzik & Anna Romanska-Zapala & Mark Bomberg, 2020. "A Neural Network for Monitoring and Characterization of Buildings with Environmental Quality Management, Part 1: Verification under Steady State Conditions," Energies, MDPI, vol. 13(13), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3469-:d:380410
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    References listed on IDEAS

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    Cited by:

    1. Marek Dudzik, 2020. "Towards Characterization of Indoor Environment in Smart Buildings: Modelling PMV Index Using Neural Network with One Hidden Layer," Sustainability, MDPI, vol. 12(17), pages 1-37, August.
    2. Mark Bomberg & Anna Romanska-Zapala & David Yarbrough, 2021. "Towards a New Paradigm for Building Science (Building Physics)," World, MDPI, vol. 2(2), pages 1-22, April.
    3. Mark Bomberg & Anna Romanska-Zapala & Paulo Santos, 2023. "The 4th Industrial Revolution Brings a Change in the Design Paradigm for New and Retrofitted Buildings," Energies, MDPI, vol. 16(4), pages 1-22, February.
    4. Przemysław Markiewicz-Zahorski & Joanna Rucińska & Małgorzata Fedorczak-Cisak & Michał Zielina, 2021. "Building Energy Performance Analysis after Changing Its Form of Use from an Office to a Residential Building," Energies, MDPI, vol. 14(3), pages 1-24, January.

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