Yönder, Veli Mustafa
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Yonder, Veli Mustafa
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veliyonder@iyte.edu.tr
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02.02. Department of Architecture
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Current Staff
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Sustainable Development Goals
1NO POVERTY
0
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2ZERO HUNGER
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3GOOD HEALTH AND WELL-BEING
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4QUALITY EDUCATION
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5GENDER EQUALITY
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6CLEAN WATER AND SANITATION
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7AFFORDABLE AND CLEAN ENERGY
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8DECENT WORK AND ECONOMIC GROWTH
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
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10REDUCED INEQUALITIES
0
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11SUSTAINABLE CITIES AND COMMUNITIES
3
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
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13CLIMATE ACTION
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14LIFE BELOW WATER
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15LIFE ON LAND
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
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17PARTNERSHIPS FOR THE GOALS
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Scholarly Output
9
Articles
2
Views / Downloads
19317/1724
Supervised MSc Theses
1
Supervised PhD Theses
1
WoS Citation Count
1
Scopus Citation Count
4
Patents
0
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0
WoS Citations per Publication
0.11
Scopus Citations per Publication
0.44
Open Access Source
5
Supervised Theses
2
| Journal | Count |
|---|---|
| 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (ECAADE) -- SEP 18-23, 2023 -- Graz Univ Technol, Graz, AUSTRIA | 2 |
| Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe | 2 |
| Engineering Proceedings | 1 |
| ICONARP International Journal of Architecture and Planning | 1 |
| Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- Workshops hosted by the 22nd International Conference on Image Analysis and Processing, ICIAP 2023 -- 11 September 2023 through 15 September 2023 -- Udine -- 306929 | 1 |
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9 results
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Now showing 1 - 9 of 9
Article Citation - WoS: 1A Case Study on Generative Building Skin Forming by Employing Building Information Modelling (bim) Tools(Konya Teknik Üniversitesi, 2020) Yönder, Veli MustafaPurposeThis study aims to produce generative curtain wall geometries based on predetermined parameterssuch as storey information, shadowzones, preliminary building unit cost, frequency, etc. in a BIM platform for the preliminary design of a future project in Basmane and understand its novel outcomes and implications. Design/Methodology/ApproachThe methodology is construed over four successive phases, namely: the built environmentmodeling, analyses for a solid understanding of the study area, determination of the generative design criteria, and finally design solutions. In the initial phase, the case-study building in Basmane with the surrounding environment was digitally modeled for the following analyses. Several programs apart from BIM have been utilized for the daylight zones and wind simulations. The daylight areas affecting the surface of the studied building were marked schematically per the simulation data. Subsequently, the area of the curtain wall, material type, preliminary building unit cost (assembly/labor and material cost), the height of storey, the density of elements, and fixed shading devices parameters were tested via optimization thru generative design methodology and provide potential design solutions by utilization of BIM tools. FindingsThe findings of this study could be boiled down to a single comprehensive objective of generating outputs of assorted design solutions thru a generative design approach. When the output data set is visualized via parallel coordinate graphs, it could be well articulated that the classification of rule-based relationships and the criteria interrelations were based on the designer's decisions. Research Limitations/ImplicationsThis study was examined on a case basis by an experimental approach. It shall be considered that the curtain wall construction encompasses diverse materials, connection details, and construction techniques that affect the final cost thus this research was conducted at the preliminary designstage and might not reflect actual costs. Social/Practical Implications Albeit the technical aspect of the curtain walls is not included in this case study, it helps generative design culture by demonstrating the extent of the opportunities it offers to designers in the preliminary design stage. Originality/Value This study is a show-case of a preliminary design for an actual building stock in the vicinity of Basmane focusing on the building envelope design process with multiple parameters and should be regarded as an opportunity to understand how innovative solutions alike are put forward for the use of designers.Conference Object Citation - Scopus: 1Classification of Turkish and Balkan House Architectures Using Transfer Learning and Deep Learning(Springer Science and Business Media Deutschland GmbH, 2024) Yönder,V.M.; İpek,E.; Çetin,T.; Çavka,H.B.; Apaydın,M.S.; Doğan,F.Classifying architectural structures is an important and challenging task that requires expertise. Convolutional Neural Networks (CNN), which are a type of deep learning (DL) approach, have shown successful results in computer vision applications when combined with transfer learning. In this study, we utilized CNN based models to classify regional houses from Anatolia and Balkans based on their architectural styles with various pretrained models using transfer learning. We prepared a dataset using various sources and employed data augmentation and mixup techniques to solve the limited data availability problem for certain regional houses to improve the classification performance. Our study resulted in a classifier that successfully distinguishes 15 architectural classes from Anatolia and Balkans. We explain our predictions using grad-cam methodology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Conference Object Decoding and Predicting the Attributes of Urban Public Spaces With Soft Computing Models and Space Syntax Approaches(Ecaade-education & Research Computer Aided Architectural design Europe, 2023) Yonder, Veli Mustafa; Dogan, Fehmi; Cavka, Hasan Burak; Tayfur, Gokmen; Dulgeroglu, OzumPeople spend a considerable amount of time in public spaces for a variety of reasons, albeit at various times of the day and during season. Therefore, it is of utmost importance for both urban designers and local authorities to try to gain an understanding of the architectural qualities of these spaces. Within the scope of this study, squares and green parks in Izmir, the third largest city in Turkey, were analyzed in terms of their dimensions, landscape characteristics, the quality of their semi-open spaces, their landmarks, accessibility, and overall aesthetic quality. Using linear predictor, general regression neural networks, multilayer feed-forward neural networks (2-3-4-5-6 nodes), and genetic algorithms, soft computing models were trained in accordance with the results of the conducted analyses. Meanwhile, using space syntax methodologies, a visibility graph analysis and axial map analysis were conducted. The training results (i.e., root mean square error, mean absolute error, bad prediction rates for testing and training phases, and standard deviation of absolute error) were obtained in a comparative table based on training times and root mean square error values. According to the benchmarking table, the network that most accurately predicts the aesthetic score is the 2-node MLFNN, whereas the 6-node MLFN network is the least successful network.Conference Object The Role of the Computational Designer From Computer-Aided Design To Machine Learning-Aided Design a Study on Generative Models and Design Prompts(Ecaade-education & Research Computer Aided Architectural design Europe, 2023) Yonder, Veli Mustafa; Dulgeroglu, Ozum; Dogan, Fehmi; Cavka, Hasan BurakThe rising sophistication of digital design technologies and instruments requires computational designers to acquire a broader set of abilities, such as expertise in a variety of digital models, scripting languages, and the ability to manage complicated data models. In the field of design, the concepts of machine learning-aided design and data-driven techniques contribute to the production of various and numerous design possibilities. Ultimately, this will lead the computational designer to redefine his or her power over the design protocol. In this paper, ChatGPT-3.5, Dall-E v2, and Stable Diffusion, cutting-edge artificial intelligence models, are used to construct sample design scenarios. Using a text mining application, the scenario-specific prompts were examined to explore these models' computational design potential.Master Thesis Archiving of the Conservation Data of Immovable Cultural Assets Dating To 1300-1600 in Urla Center Using Gis(Izmir Institute of Technology, 2019) Yönder, Veli Mustafa; Turan, Mine; Demirkesen, Ali CanThis study aims to create a digital archiving system of immovable cultural assets belonging to the early Turkish time frame in Urla historic center. Forming a database with the assistance of the Geographic Information System (GIS) to comprehend and assess the life stories of monuments and to access various user profiles is also considered. In the methodology section; academic articles, books, journals, personal archives, data acquired from state institutions or architectural offices, and the data obtained during fieldwork (physical status and interviews with users) were processed in a GIS platform. Academic reviews and researches of the buildings were conducted. In the decision-making process, which is a sophisticated and multidimensional process, the share of conservation data and data management in the whole process becomes progressively significant. Documentation and registration of architectural immovable cultural assets, which is one of the important figures in the urban context, are conducted under the supervision of the Regional Directorate of Pious Foundations or the Conservation Board. Therefore, extracting a large number of mass data produced each year and making the required classifications make assist decision-making processes. In the discussion and results part, analysis and comparative study of all conservation data of the cultural assets were performed. The results for constructing the database are understanding the scope, accessibility, developers, scale, and data types. In the results for the conservation data archived: are understanding historical background, physical characteristics, conservation activities, and interpreting conservation decisions about buildings.Conference Object Citation - Scopus: 2The Role of the Computational Designer From Computer-Aided Design To Machine Learning-Aided Design a Study on Generative Models and Design Prompts(Education and research in Computer Aided Architectural Design in Europe, 2023) Yonder, V.M.; Dulgeroglu, O.; Dogan, F.; Cavka, H.B.The rising sophistication of digital design technologies and instruments requires computational designers to acquire a broader set of abilities, such as expertise in a variety of digital models, scripting languages, and the ability to manage complicated data models. In the field of design, the concepts of machine learning-aided design and data-driven techniques contribute to the production of various and numerous design possibilities. Ultimately, this will lead the computational designer to redefine his or her power over the design protocol. In this paper, ChatGPT-3.5, Dall-E v2, and Stable Diffusion, cutting-edge artificial intelligence models, are used to construct sample design scenarios. Using a text mining application, the scenario-specific prompts were examined to explore these models' computational design potential. © 2023, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Article Understanding the Impact of Deep Learning Models on Building Information Modeling Systems: a Study on Generative Artificial Intelligence Tools †(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Yönder,V.M.The power of the relationship between building information modeling (BIM) systems and advanced artificial intelligence models holds considerable weight for users of BIM. This relationship allows the generation, analysis, and deduction of insights from substantial construction digital data. This research explores the relationship between generative artificial intelligence (generative AI), deep neural nets, and the BIM systems, including its users. This study examines the correlation between generative artificial intelligence and BIM methodology by conducting a case study. Furthermore, this paper investigates the conceptual and practical use of generative AI components (e.g., text-to-image models, diffusion networks, deep neural networks, large language model, and generative adversarial network) in BIM systems via bibliometric analysis. © 2023 by the author.Doctoral Thesis Somut Mimari Miras Verilerinin Derin Öğrenme Tabanlı Görsel Analizi: Osmanlı Vernaküler Konutlarının Cephe Görselleri Üzerinden Sınıflandırılması(2025) Yönder, Veli Mustafa; Doğan, Fehmi; Çavka, Hasan BurakBu çalışma, somut kültürel miras verilerinin görsel analizinde önceden eğitilmiş derin öğrenme modellerinin ve verinin rolünü ve etkinliğini Osmanlı vernaküler konutlarının cephe görselleri aracılığıyla araştırmaktadır. Mimari miras verileri doğası gereği çok katmanlı ve çok boyutludur ve güncel literatür, hesaplamalı yöntemlerle (örn. parametrik modelleme, biçim grameri ve mekân dizimi) ve dijital çerçevelerle (örn. tarihi yapı bilgi modellemesi ve tarihi coğrafi bilgi sistemleri) artan ilişkisini ortaya koymuştur. Bu kapsamda, derin öğrenme temelli yaklaşımlar, karmaşık mimari veri kümelerini analiz etmek için yeni fırsatlar sunmaktadır. Anadolu ve Balkanlar'daki geleneksel evlerin cephe fotoğraflarından derlenen bir veri seti oluşturulmuştur. Model performansının veri kalitesine olan hassasiyeti nedeniyle, çoklu iş akışı diyagramları ve veri toplama protokolü geliştirilmiştir. Veri kümesi eğitim (%70), doğrulama (%20) ve test (%10) alt kümelerine ayrılmış ve sınırlı büyüklüğü nedeniyle çeşitli teknikler (örn. Mixup) kullanılarak artırılmıştır. Konvolüsyonel sinir ağı tabanlı mimariler (örn. ResNet ve ConvNeXt) ve dönüştürücü tabanlı modeller (örn. Swin Transformer ve DeiT), transfer öğrenme ve ince ayar stratejileri ile kullanılmıştır. Yığın boyutu, öğrenme oranı, epok sayısı ve optimizasyon fonksiyonu gibi hiperparametreler üzerinde çalışılmıştır. Grad-CAM, Açıklanabilir Yapay Zekâ çerçevesinde kullanılmıştır. Görüntü bulma görevi ön eğitimli derin öğrenme modeli ile gerçekleştirilmiştir. Ayrıca, benzer mimari özelliklere sahip veriler gruplandırılarak mimari süper sınıflar oluşturulmuş ve 2B ortamdaki dağılımlarını görselleştirmek için t-SNE uygulanmıştır. Denetimli sınıflandırma gerçekleştirilmiş ve model performansı doğrulama ve test doğruluğu, MCC skoru gibi ölçütler kullanılarak değerlendirilmiştir. Ayrıca, her bir ince ayarlı model için makro ağırlıklı hassasiyet, geri çağırma ve F1-Skor değerleri elde edilmiştir. Mimari miras veri kümesinin oluşturulması, veri toplama protokolünün formüle edilmesi, semantik süper sınıfların tasarımı ve derin öğrenme tabanlı iş akışlarının geliştirilmesi başlıca çıktılar arasında yer almaktadır.Conference Object Citation - Scopus: 1Decoding and Predicting the Attributes of Urban Public Spaces With Soft Computing Models and Space Syntax Approaches(Education and research in Computer Aided Architectural Design in Europe, 2023) Yönder, Veli Mustafa; Doğan, Fehmi; Çavka, Hasan Burak; Tayfur, Gökmen; Dülgeroğlu, ÖzümPeople spend a considerable amount of time in public spaces for a variety of reasons, albeit at various times of the day and during season. Therefore, it is of utmost importance for both urban designers and local authorities to try to gain an understanding of the architectural qualities of these spaces. Within the scope of this study, squares and green parks in Izmir, the third largest city in Turkey, were analyzed in terms of their dimensions, landscape characteristics, the quality of their semi-open spaces, their landmarks, accessibility, and overall aesthetic quality. Using linear predictor, general regression neural networks, multilayer feed-forward neural networks (2-3-4-5-6 nodes), and genetic algorithms, soft computing models were trained in accordance with the results of the conducted analyses. Meanwhile, using space syntax methodologies, a visibility graph analysis and axial map analysis were conducted. The training results (i.e., root mean square error, mean absolute error, bad prediction rates for testing and training phases, and standard deviation of absolute error) were obtained in a comparative table based on training times and root mean square error values. According to the benchmarking table, the network that most accurately predicts the aesthetic score is the 2-node MLFNN, whereas the 6-node MLFN network is the least successful network. © 2023, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.