Issue |
E3S Web Conf.
Volume 49, 2018
SOLINA 2018 - VII Conference SOLINA Sustainable Development: Architecture - Building Construction - Environmental Engineering and Protection Innovative Energy-Efficient Technologies - Utilization of Renewable Energy Sources
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Article Number | 00125 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/e3sconf/20184900125 | |
Published online | 13 August 2018 |
Using Artificial Intelligence in energy efficient construction
Faculty of Civil Engineering, Warsaw University of Technology, Warsaw, Poland
* Corresponding author: a.weglarz@pw.edu.pl
Artificial Neural Networks (ANNs), genetic algorithms, case based reasoning (CBR), and hybrid systems are all methods of artificial intelligence. This dissertation presents a literature overview and its author’s achievements in methods of utilizing artificial intelligence methods in energy efficient buildings, which include: an expert system for supporting the financing of thermo-modernization investment, a method of optimizing thermo-modernization strategies for groups of buildings using genetic algorithms, and a case based reasoning system (CBR) intended to facilitate the design of energy efficient single family housing. Case based reasoning consists of comparing new problems with past problems and using a past solution. In the CBR system, previously developed single family housing designs will be described using linguistic variables defined as fuzzy sets. The designer, who wants to create the documentation for a new energy efficient building after talking with the investor about his or her expectations, enters a query, defined as linguistic variables, into the system. The system finds the documentation of already constructed buildings, most closely matching the investor’s requirements. The designer performs the required adjustments, and after the investor’s approval, places the new documentation into the database for further use.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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