Mimar Sinan Güzel Sanatlar Üniversitesi Açık Bilim, Sanat Arşivi
Açık Bilim, Sanat Arşivi, Mimar Sinan Güzel Sanatlar Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.MSGSÜ'de Ara
Yazar "Aydın, Yaren" için listeleme
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Adaptive Neural Architecture Search Using Meta-Heuristics: Discovering Fine-Tuned Predictive Models for Photocatalytic CO2 Reduction
Işıkdağ, Ümit; Bekdaş, Gebrail; Aydın, Yaren; Apak, Sudi; Hong, Junhee; Geem, Zong Woo (Multidisciplinary Digital Publishing Institute (MDPI), 2024)This study aims to contribute to the reduction of carbon dioxide and the production of hydrogen through an investigation of the photocatalytic reaction process. Machine learning algorithms can be used to predict the hydrogen ... -
Application of adaptive harmony search and machine learning on optimization problems about strength of materials
Aydın, Yaren; Niğdeli, Sinan Melih; Bekdaş, Gebrail; Işıkdağ, Ümit; Geem, Zong Woo (Metaheuristics-Based Materials Optimization, 2025)In structural design, the strength of materials is the key factor in design and applications including optimization covers the strength of material theory in design. The constraints are generally related to the strength ... -
Comparison of Multilayer Perceptron and Other Methods for Prediction of Sustainable Optimum Design of Reinforced Concrete Columns
Aydın, Yaren; Bekdaş, Gebrail; Nigdeli, Sinan Melih; Işıkdağ, Ümit; Geem, Zong Woo (Springer Science and Business Media Deutschland GmbH, 2023)Machine learning has become a popular science in recent years, as it produces concrete and fast solutions to solve many problems. The rapidly increasing world population and the developments in technology have caused large ... -
Fire Resistance Prediction in FRP-Strengthened Structural Elements: Application of Advanced Modeling and Data Augmentation Techniques
In order to ensure the earthquake safety of existing buildings, retrofitting applications come to the fore in terms of being fast and cost-effective. Among these applications, fiber-reinforced polymer (FRP) composites are ... -
Predicting the area moment of inertia of beam and column using machine learning and HyperNetExplorer
Aydın, Yaren; Niğdeli, Sinan Melih; Roozbahan, Mostafa; Bekdaş, Gebrail; Işıkdağ, Ümit (Springer, 2025)Beams and columns are the most important elements of steel frame structures. Damage to the beam or column can lead the structure to serious hazards and cause collapse. In the structural engineering literature, it has been ... -
A Real-Time Advisory Tool for Supporting the Use of Helmets in Construction Sites
Işıkdağ, Ümit; Çemrek, Handan As; Sönmez, Seda; Aydın, Yaren; Bekdaş, Gebrail; Geem, Zong Woo (2025)In the construction industry, occupational health and safety plays a critical role in preventing occupational accidents and increasing productivity. In recent years, computer vision and artificial intelligence-based systems ... -
Shear Wave Velocity Prediction with Hyperparameter Optimization
Bekdaş, Gebrail; Aydın, Yaren; Isikdag, Umit; Nigdeli, Sinan Melih; Hajebi, Dara; Kim, Tae-Hyung; Geem, Zong Woo (Multidisciplinary Digital Publishing Institute (MDPI), 2025)Shear wave velocity (Vs) is an important soil parameter to be known for earthquake-resistant structural design and an important parameter for determining the dynamic properties of soils such as modulus of elasticity and ... -
Use of Machine Learning Techniques in Soil Classification
Aydın, Yaren; Işıkdağ, Ümit; Bekdaş, Gebrail; Nigdeli, Sinan Melih; Geem, Zong Woo (Multidisciplinary Digital Publishing Institute (MDPI), 2023)In the design of reliable structures, the soil classification process is the first step, which involves costly and time-consuming work including laboratory tests. Machine learning (ML), which has wide use in many scientific ...
