Journal
12TH INTERNATIONAL CONFERENCE INTERDISCIPLINARITY IN ENGINEERING (INTER-ENG 2018)
Volume 32, Issue -, Pages 434-441Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.promfg.2019.02.237
Keywords
Applied artificial intelligence; Building heat losses prediction; Ground time-dependent heat transfer; Neural networks; Numerical analysis
Funding
- Technical University of Cluj-Napoca [1987/12.07.2017]
Ask authors/readers for more resources
One of the most important directions towards global CO2 emissions and primary energy consumption reduction is to increase energy efficiency in the sector of residential and non-residential buildings. The evaluation of building envelope heat losses through ground, as part of the building energy demand and energy consumption, it still has a lack of comprehensive knowledge relative to the large buildings. This article aims to use artificial neural networks (ANNs) to allow long-term prediction of the heat transfer losses through ground during heating season for the large dimensions slabs, which are specific for many non-residential buildings, in order to reduce the significant resources needed for the numerical analysis in time-dependent state. A hybrid approach is proposed by developing an application to study a less investigated area of civil engineering. (C) 2019 The Authors. Published by Elsevier Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available