7th International Electronic Conference on Sensors and Applications 2020
DOI: 10.3390/ecsa-7-08272
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Application of Multilayer Perceptron Method on Heat Flow Meter Results for Reducing the Measurement Time

Abstract: To reduce the impact on climate change, many countries have developed strategies for the building sector with a goal to reduce the energy demands and carbon emission of buildings. As most buildings that exist today will very likely exist in foreseeable future, many buildings will need to undergo major renovations. One of the most important parameters in determining the transmission heat losses through the building envelope is the U-value, i.e., thermal transmittance, and it is simply the rate of heat transfer … Show more

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Cited by 6 publications
(8 citation statements)
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“…The training process can be considered as adjusting the model weights and biases with the goal of minimizing a cost function [36][37][38]. The most important part of network design and performance is the adequate selection of the inputs and the preparation of the training set.…”
Section: Ai-powered Distance Estimation Systemmentioning
confidence: 99%
“…The training process can be considered as adjusting the model weights and biases with the goal of minimizing a cost function [36][37][38]. The most important part of network design and performance is the adequate selection of the inputs and the preparation of the training set.…”
Section: Ai-powered Distance Estimation Systemmentioning
confidence: 99%
“…Recently, the work by Tejedor et al [5] introduces the future perspectives of the DL method for the diagnosis of heritage buildings. The methods reviewed in the paper cover several important topics, e.g., object detection which can be integrated with UAVs and a GPS system [6], 3D models for the reconstruction of lost architectural heritage [7], and neural networks applied to heat flux meter (HFM) methods [8,9]. Some defects of the DL method are also given in the paper, especially the limitation of dataset and computation time cost.…”
Section: Introductionmentioning
confidence: 99%
“…We can measure more than one element at a time with multiple HFM devices, but this way is financially and operationally inefficient [34]. On the other hand, there are examples in the literature of shortening the measurement time by applying artificial-intelligence (AI) models to the results to predict the resulting U-value based on in-situ methods [35][36][37][38][39].…”
Section: Introductionmentioning
confidence: 99%
“…These predicted heat-flux time series are then used to determine the U-value. The models from [37,38] have two input parameters-outdoor and indoor air temperature-and the resulting heat flux is predicted. In this case, differences from 0.78% to 8.73% can be obtained with respect to HFM measurements.…”
Section: Introductionmentioning
confidence: 99%
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