Al-Magsoosi, Ali Habeeb Askar and Kovács, Endre and Bolló, Betti (2023) Multi objective optimization for house roof using artificial neural network model. MULTIDISZCIPLINÁRIS TUDOMÁNYOK: A MISKOLCI EGYETEM KÖZLEMÉNYE, 13 (2). pp. 11-25. ISSN 2062-9737
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Abstract
Roof models with low heat loss and low heating costs for buildings are crucial for reducing energy consumption and greenhouse gas emissions in cold regions. This study aimed to calculate the heat loss for various roof models with low heat loss, which are widely used in houses in Europe and other cold regions. We created 324 models for three types of roofs (light, medium, and heavy) with different materials and thicknesses using the HAP program. We then trained a neural network (ANN) to generate a mathematical function that can be used to calculate the optimal surface using a multi-objective genetic algorithm method. The resulting optimal roof design was simulated using the Ansys program on a January day. We compared the heat loss results for the optimal roof for HAP, ANN, and transient thermal analysis by Ansys, respectively, showing a close agreement among the methods.
Item Type: | Article |
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Uncontrolled Keywords: | multi-objective genetic algorithm, roof design, optimization, heating load, insulated roof |
Subjects: | Q Science / természettudomány > Q1 Science (General) / természettudomány általában |
SWORD Depositor: | MTMT SWORD |
Depositing User: | MTMT SWORD |
Date Deposited: | 24 Apr 2024 13:54 |
Last Modified: | 24 Apr 2024 13:54 |
URI: | https://real.mtak.hu/id/eprint/193112 |
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