Using Artificial Intelligence in energy efficient construction

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...

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Main Author: Węglarz Arkadiusz
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:E3S Web of Conferences
Online Access:https://doi.org/10.1051/e3sconf/20184900125
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spelling doaj-8a53f7a361a245eeae4f1a8f3418eda02021-02-02T07:58:53ZengEDP SciencesE3S Web of Conferences2267-12422018-01-01490012510.1051/e3sconf/20184900125e3sconf_solina2018_00125Using Artificial Intelligence in energy efficient constructionWęglarz ArkadiuszArtificial 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.https://doi.org/10.1051/e3sconf/20184900125
collection DOAJ
language English
format Article
sources DOAJ
author Węglarz Arkadiusz
spellingShingle Węglarz Arkadiusz
Using Artificial Intelligence in energy efficient construction
E3S Web of Conferences
author_facet Węglarz Arkadiusz
author_sort Węglarz Arkadiusz
title Using Artificial Intelligence in energy efficient construction
title_short Using Artificial Intelligence in energy efficient construction
title_full Using Artificial Intelligence in energy efficient construction
title_fullStr Using Artificial Intelligence in energy efficient construction
title_full_unstemmed Using Artificial Intelligence in energy efficient construction
title_sort using artificial intelligence in energy efficient construction
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2018-01-01
description 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.
url https://doi.org/10.1051/e3sconf/20184900125
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