The mechanical behaviour of the wall, in-situ wall tests and numerical analysis is required along with the material properties. With the support of smart learning techniques, the state of the walls was estimated. This makes it possible to obtain healthy data to support the experiment and modelling. The utilization of mathematical tools like Fuzzy Logic has been demonstrated to be beneficial in resolving intricate engineering issues, without the need to replicate the studied phenomenon, given that the only available information consists of the problem's parameters and desired outcomes. To analyse the wall's behaviour more accurately and quickly, analyses were made using the fuzzy method, one of the smart learning techniques, and compared with the data in the studies in which experimental analysis was applied. The behaviour of the wall, the flexibility and energy capacity were tried to be estimated. In the fuzzy, material parameters and wall load capacities that will affect the properties of the wall are used as inputs. Thirty-five (35) data sets, experiments and modelling data from different studies were taken. Estimation results were compared with empirical results.
The mechanical behaviour of the wall, in-situ wall tests and numerical analysis is required along with the material properties. With the support of smart learning techniques, the state of the walls was estimated. This makes it possible to obtain healthy data to support the experiment and modelling. The utilization of mathematical tools like Fuzzy Logic has been demonstrated to be beneficial in resolving intricate engineering issues, without the need to replicate the studied phenomenon, given that the only available information consists of the problem's parameters and desired outcomes. To analyse the wall's behaviour more accurately and quickly, analyses were made using the fuzzy method, one of the smart learning techniques, and compared with the data in the studies in which experimental analysis was applied. The behaviour of the wall, the flexibility and energy capacity were tried to be estimated. In the fuzzy, material parameters and wall load capacities that will affect the properties of the wall are used as inputs. Thirty-five (35) data sets, experiments and modelling data from different studies were taken. Estimation results were compared with empirical results.
Primary Language | English |
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Subjects | Environmentally Sustainable Engineering, Electrical Engineering (Other) |
Journal Section | Research Article |
Authors | |
Publication Date | December 31, 2023 |
Submission Date | December 20, 2023 |
Acceptance Date | December 31, 2023 |
Published in Issue | Year 2023 Volume: 03 Issue: 02 |
The journal "Researcher: Social Sciences Studies" (RSSS), which started its publication life in 2013, continues its activities under the name of "Researcher" as of August 2020, under Ankara Bilim University.
It is an internationally indexed, nationally refereed, scientific and electronic journal that publishes original research articles aiming to contribute to the fields of Engineering and Science in 2021 and beyond.
The journal is published twice a year, except for special issues.
Candidate articles submitted for publication in the journal can be written in Turkish and English. Articles submitted to the journal must not have been previously published in another journal or sent to another journal for publication.