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Experimental buildings for "in situ" research are a very important tool for collecting data on energy efficiency of the energy-saving technologies. One of the most advanced building of this type in Poland is the Maloposkie Laboratory of Energy-saving Buildings at Cracow University of Technology. The building itself is used by scientists as a resear...
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... The solution presented in the article is a continuation of many years of research, which was the basis for the creation of many articles. In previous studies [25][26][27][28][29][30], the experimental base was discussed in detail along with the possibilities it creates for conducting "in situ" research in the field of automatic process control. The issues concerning the work of individual technical systems (HVAC, lighting, blinds, etc.) in terms of reducing energy consumption through the implementation of specially developed control algorithms are presented elsewhere (see [6,26,[31][32][33]), as are issues related to providing comfort in an energy-efficient building (see [10,29,30,34,35]). ...
... In the previous series of papers, we addressed the issues related to the next generation of construction technology from a building science point of view [1][2][3][4][6][7][8]. This paper, as well as two more papers to follow, will address the issues related to the building automation, controls, and building management systems that as we know [25,39,40] may have an impact on both energy efficiency and building science. This paper employs two types of verification: (1) traditional verification of ANNs that includes a validation stage after training and before testing, and (2) comparison of the measured and ANN calculated results. ...
... Figure 5 eliminates s {1} = 9, 12, 16, 18, 20, 23, 28, 31 and Figure 6, for s {1} = 6,9,11,12,16,18,20,21,22,23,28,30 because they had too wide of an interquartile range (IQR) (i.e., differences were too large versus the median) [24]. Effectively, only the structures s {1} = 8, 10,13,14,15,17,24,25,26,27,29 can be considered as suitable. ...
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.
