Using Artificial Intelligence in energy efficient construction

Arkadiusz Węglarz

Abstract

Artificial Neural Networks (ANNs), genetic lgorithms, 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 b ased 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 documentat ion 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 doc umentation 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
Author Arkadiusz Węglarz (FCE / ICE)
Arkadiusz Węglarz,,
- The Institute of Civil Engineering
Journal seriesE3S Web of Conferences, ISSN 2267-1242, (0 pkt)
Issue year2018
Vol49
Pages1-9
Publication size in sheets0.5
ConferenceVII Conference SOLINA Sustainable Development: Architecture - Building Construction - Environmental Engineering and Protection Innovative Energy-Efficient Technologies - Utilization of Renewable Energy Sources (Solina 2018), 19-06-2018 - 23-06-2018, Solina, Polska
Keywords in Polishtermomodernizacja
Keywords in Englishenergy efficient buildings, thermo-modernization investment,
URL https://doi.org/10.1051/e3sconf/20184900125
Languageen angielski
File
solina2018_00125.pdf 470.08 KB
Score (nominal)5
ScoreMinisterial score = 0.0, 11-09-2018, ArticleFromJournal
Ministerial score (2013-2016) = 5.0, 11-09-2018, ArticleFromJournal - czasopismo zagraniczne spoza list
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