Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object A General Predictive Model to Evaluate Daylight Levels of Residential Buildings in the Mediterranean (Next Med) Region(Education and Research in Computer Aided Architectural Design in Europe, 2025) Ekici, B.Conceptual design is one of the most critical phases, as design decisions affect the buildings’ performance throughout their life cycle. Researchers consider various computational methods to achieve effective design proposals. Nevertheless, optimization algorithms are necessary to cope with the complexity and increase the efficiency of design alternatives in various aspects. In sustainable building design, these decisions require computationally expensive processes due to the simulation tasks. Besides, making sustainable design decisions is even more challenging in a Mediterranean climate due to changing conditions throughout the year. Therefore, recent studies frequently consider combining predictive models with optimization algorithms to decrease the burden of expensive simulation time. Relevant works present promising outcomes, yet they are limited to predicting the building performance of specific cases; thus, the proposed predictive models are limited to different design problems. This paper investigates the development of a general machine learning (ML) model to overcome this issue. With this motivation, a parametric test box consisting of twenty parameters related to weather data of twelve Mediterranean (Next Med) countries, space dimensions, vertical/horizontal louvers, and material type is developed using Grasshopper 3d. Moreover, a parametric urban model, which considers eight parameters related to the density of the surrounding buildings, is also created to generate numerous environments. The LadyBug tools simulate the daylight autonomy to generate 12,000 samples. Five different ML models involving artificial neural networks (ANN) are built in Python. Statistical results showed that train and test scores achieved promising outcomes in all ML models. However, when predicting user-defined scenarios not involved in the generated dataset, only ANNs perform generalizable, accurate predictions. The paper discusses the ability of ANN models to accurately predict different design scenarios and locations, and the trustworthiness of the training and test scores based only on collected data. © 2025, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Conference Object Metacognitive, Cognitive, and Creative Dynamics in the Artificial Intelligence-Aided Design Process(Education and Research in Computer Aided Architectural Design in Europe, 2025) Yazici, G.; Doǧan, F.This study examines the effects of artificial intelligence-aided design processes (AIADP) on cognitive load, creativity, and metacognitive awareness. Within the scope of the study, a one-day face-to-face workshop was organised with twenty-eight architects, including architecture students studying at undergraduate and graduate levels, and the data based on the participants' experiences were analysed using qualitative research methods. The results of the sentiment-based content analysis show that integrating AI tools into the design process reduces cognitive load, supports creative thinking processes, facilitates rapid prototyping and feedback mechanisms, and increases metacognitive awareness. The findings reveal that AI-aided design tools can potentially improve designers' cognitive and creative capacities. The study addresses the effects of AIADP in educational and professional contexts from a local perspective, providing a new perspective on the literature on the integration of AI into design processes. © 2025, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Book Part Greenmetric Journey of Izmir Institute of Technology: Agile Strategies Towards a Green Campus(Springer Science and Business Media Deutschland GmbH, 2026) Keskin, E.; Ökten, H.E.; Akpinar, İ.; Baran, Y.Recently, there has been growing attention towards sustainable approaches on university campuses through disseminating international evaluation systems, the UI GreenMetric World University Rankings (GM) attracting specific attention in particular. Türkiye is one of the countries where the number of participating universities in GM rises annually at a significant pace. Most of the large-scale university campuses in Türkiye were already built by the 1990s, which led these campuses to adapt themselves to higher standards for sustainability. In this context, Izmir Institute of Technology (IZTECH), a 33-year-old university, has applied for the GM with its Gülbahçe Campus since 2020. This paper aims to reveal IZTECH’s institutional agile sustainability strategy, energetic and collective processes, and good practices in the last five years while examining the outcomes through the GM’s evaluation of six assessment criteria. In this regard, the sustainability practices of IZTECH have been monitored since 2019 and compared to how the developments have improved the GM scores for the past 3 years. This study, focusing on the IZTECH campus through historical, social, educational, and technological perspectives, unveils the barriers between developing and implementing sustainability practices and examines the cohesion between GM scores and annual reports of campus activities for further projections towards a greener campus. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.Conference Object Assessment of Drought in Izmir District Using Standardized Precipitation Index(Springer Nature, 2025) Mersin, D.; Gulmez, A.; Safari, M.J.S.; Vaheddoost, B.; Tayfur, G.One of the main issues with agro-food and socio-economical security in the world is droughts. Regardless of cause or effect, the ever-changing climate is placing increasing strain on water resources pushing supply to its limits. Izmir, a growing city in Turkey, is endowed with variety of water resources, such as lakes, rivers, seashores, and groundwater reserves. Therefore, it is crucial for the planning and development of the area to examine past and foreseeable drought occurrences and their possible impact on water resources. In this regard, the study’s goal is to assess historical droughts in Izmir District. Data from three meteorological stations in Küçük Menderes basin, collected between 1973 and 2020, are utilized in this study. To establish the validity of the posterior drought analysis, the consistency and trend in the time series are first examined using the double mass curve, run test, and linear trend analysis. The next step is to assess the historical deficit related to meteorological, agricultural, and hydrological droughts using the SPI and moving mean (MA) operator. The temporal analysis of SPI reveals distinct drought patterns across the stations, with multiple moderate to extreme droughts occurring particularly between 1998 and 2010, highlighting significant spatial and temporal variability in drought severity and frequency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Conference Object An Experimental Study to Investigate the Efficiency of Floating Pontoons on the Wave Overtopping Reduction(International Society of Offshore and Polar Engineers, 2025) Ozbahceci, B.O.; Eroglu, N.There are many studies focused on the wave transmission performance of floating structures. However, the performance of floating structures to prevent coastal floods has not yet been investigated considering wave overtopping. This study aimed to experimentally assess the wave overtopping performance of a concrete floating pontoon in front of an existing vertical sea wall. The mean wave overtopping discharge, q, was compared for the cases with and without the floating pontoon model in front of the wall. Results showed that the baseline floating pontoon model reduced wave overtopping discharge by 30-90% compared to the case with the wall alone. Furthermore, the study revealed that an increase in freeboard or draft of the floating pontoon led to a greater reduction in wave overtopping. These findings suggest that the integration of a floating pontoon with optimized freeboard and draft could be an effective solution for reducing wave overtopping in coastal defense applications. © 2025 by the International Society of Offshore and Polar Engineers (ISOPE).Conference Object Developing Machine Learning Models to Predict Outdoor Thermal Comfort of Kinetic Shading Devices: An Approach for Global Optimization(Education and Research in Computer Aided Architectural Design in Europe, 2025) Dağlier, Y.; Ekici, B.; Korkmaz, K.Utilizing artificial intelligence (AI) methods in the design process supports the achievement of sustainable alternatives during the conceptual design. In various AI methods, optimization and machine learning (ML) algorithms are the most common methods to develop predictive models and discover favorable design alternatives with significantly reduced computational time. Recent works focused on limited datasets, as well as the evaluation of the developed prediction models based on collected data. During the optimization process of complex design problems, the number of design parameters becomes enormous; thus, search areas contain many design alternatives that might lead the search outside of the collected data. Therefore, evaluating the accuracy of prediction models only based on the collected samples may result in scenarios where the predicted outcome during the optimization process aligns with an unrealistic solution. This study investigates how accurately prediction models developed using different ML algorithms can perform in optimization processes. The proposed framework is used to cope with outdoor thermal performance, considering kinetic shading devices with rigid origami techniques. A parametric shading device model with kinematic principles and 10 design parameters is created in Grasshopper 3d. LadyBug is used to analyze the performance of the universal thermal climate index (UTCI). To minimize the UTCI, the radial basis function optimization (RBFOpt) algorithm in the Opossum plugin is used. To compare the optimization results with the prediction results, multiple linear regression, support vector machines, random forest, polynomial regression algorithms, and artificial neural networks (ANN) are developed to predict outdoor thermal comfort performance targets on each collected data set with 2000 samples. Results showed that ANN models can provide more accurate predictions during the optimization process. The paper aims to discuss the way ML algorithms are applied and evaluated for ML-based optimization domains in design problems. © 2025, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Conference Object Combining Generative Adversarial Networks and Reinforcement Learning for Floor Plan Layout Generation(Education and Research in Computer Aided Architectural Design in Europe, 2025) Güldilek, M.; Ilal, M.E.; Ekici, B.Generative Adversarial Networks (GANs) are among artificial intelligence (AI) methods for generating architectural floor plan layouts to approximate spatial distribution with a reasonable degree of accuracy. However, when used exclusively, GAN-based tools may fail to capture architectural patterns and often produce unrealistic layouts. To address this limitation, researchers have proposed integrating Reinforcement Learning (RL) into GANs. While RL has been combined with generative algorithms in other fields, a systematic multi-scenario integration of GANs and RL remains underexplored in architecture. This paper introduces a new solution by combining RL and GANs to generate floor plan layouts tailored to user requirements. The research design involves three different integration strategies: (1a) mere generation, where RL refines GAN outputs by eliminating inconsistencies and errors; (1b) objective optimization, where RL targets measurable attributes such as spatial size and morphological legibility; and (1c) refinement of non-quantifiable attributes, where RL incorporates user feedback to improve flexibility and perceived comfort. Additionally, the study employs House-GAN++ as the GAN model and the PPO algorithm as the RL framework. Three case studies are presented to evaluate performance. Results demonstrate that integrating RL with GANs yields floor plan layouts more responsive to user needs than those produced by GANs alone. Each scenario illustrates how RL optimizes GAN-generated outputs according to functional, measurable, and perceptual goals. The methodology acknowledges user expectations and translates them into realistic, adaptable plans. Key outcomes include more realistic layouts, designs with distinctive characteristics, and user-customized floor plans created through interaction. The proposed framework enables automatic floor plan generation that combines design, optimization, and user input at the conceptual stage. This integration enhances architectural design processes by balancing computational efficiency with user-oriented adaptability, thus broadening the potential of AI-assisted design. © 2025, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Conference Object Collabpersona: A Framework for Collaborative Decision Analysis in Persona Driven LLM-Based Multi-Agent Systems(IEEE Computer Society, 2025) Tamer, O.A.; Gumus, A.Large Language Model (LLM) agents have recently demonstrated impressive capabilities in single agent and adversarial settings, but their ability to collaborate effectively with minimal communication remains uncertain. We introduce CollabPersona, a simulation framework that combines persona-grounded memory with one-shot feedback to study team-based reasoning among LLM agents. In a multi-round variant of the Guess 0.8 of the Average game, agents reason entirely through structured prompts without fine-tuning. Our results show that minimal feedback significantly improves intra-team coordination and stabilizes strategic behavior, while cognitive style remains a primary driver of competitive outcomes. These findings suggest that lightweight scaffolding can elicit emergent collaboration in LLM agents and provide a flexible platform for studying cooperative intelligence. © 2025 IEEE.Conference Object Strengthening of Reinforced Concrete Columns Using Recycled Polyethylene Terephthalate Fibers: A Preliminary Numerical Study(fib. The International Federation for Structural Concrete, 2025) Dalgic, K.D.; Gozun, U.; Simsek, B.; Sencar, I.; Ispir, M.; Ilki, A.Strengthening of reinforced concrete (RC) columns, which have inadequate capacities of deformation and axial/lateral load, using carbon fiber reinforced polymers (CFRP) has become widespread. However, concerns about cost, energy sustainability and environmental impact have led to increased interest in alternative fibers, such as recycled polyethylene terephthalate (PET) fibers, instead of high-tech, carbon-intensive materials. This study presents preliminary numerical analyses on the use of PET fibers recycled from tire industry waste in Türkiye to strengthen substandard RC columns. The numerical analyses of the column models were performed under axial and horizontal loads. The results show that even small amounts of PET-FRP fibers can significantly improve both lateral load and deformation capacities of RC column, indicating the development of strengthening strategies for upcoming column tests. Based on the results of numerical studies, an experimental program for quasistatic testing of substandard RC columns has been planned. © 2025 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 1Binet–Fibonacci Calculus and N = 2 Supersymmetric Golden Quantum Oscillator(Springer International Publishing AG, 2025) Pashaev, Oktay K.The Binet-Fibonacci calculus, as phi phi'-two base quantum calculus, relates Fibonacci derivative with Binet formula of Fibonacci number operator, acting in Fock space of quantum states. It provides a tool to study the Golden oscillator with energy spectrum in form of Fibonacci numbers. Here we generalize this model to supersymmetric number operator and corresponding Binet formula for supersymmetric Fibonacci operator F-N. It determines the Hamiltonian of supersymmetric Golden oscillator, acting in. H-f circle times H-b-fermion-boson Hilbert space and belonging to N = 2 supersymmetric algebra. Trace on fermions of this model reduces the Hamiltonian to the Golden oscillator. The eigenstates of the super Fibonacci number operator are double degenerate and can be characterized by a point of the super-Bloch sphere. By the supersymmetric Fibonacci annihilation operator, we construct the coherent states as eigenstates of this operator. Entanglement of fermions with bosons in these states is calculated by the concurrence, represented by the Gram determinant and Fibonacci exponential functions. These functions have been appeared as descriptive for inner product of the Golden coherent states in Fock-Bargmann representation. The reference state, coming from the limit alpha -> 0 and corresponding von Neumann entropy, measuring fermion-boson entanglement, are characterized by the Golden ratio.