Browsing by Author "Cagdas, Gulen"

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Citation - WoS: 22
Citation - Scopus: 30
Fuzzy logic in agent-based modeling of user movement in urban space: Definition and application to a case study of a square
(Elsevier Ltd, 2020) Berfin Yıldız; Gulen Cagdas; Yildiz, Berfin; Cagdas, Gulen
The growing complexity of design processes increases the distance between designer and user which makes it challenging to consider user experience in design. Computational models can help us to simulate user behaviors where agents represent users as a collection of autonomous decision-making entities. In this context development of these models supports early stage decision-making in urban design. The aim of this study is to investigate how the user is involved in urban space and to analyze the relationship between urban space components and the users’ movement to be able to develop a model for user movement simulation. This paper follows a five-step consecutive process: (1) data collection with observation studies and environmental analysis (2) interpretation of the data using fuzzy logic (3) agent-based model development (4) model implementation (5) evaluation and validation. The interpretation of the observation data is to calculate the attractiveness value of urban space components with fuzzy logic. The value is then defined as attract force on agent-based simulation model. The simulation results are evaluated comparatively using observation outputs. As a case study for the model capabilities demonstration a square is chosen (Konak Square Izmir Turkey). Two models for morning and evening timelines are defined and tested to be able to simulate user movement in the square. Thereafter the efficiency of the model is examined by comparing the simulation results and observation data by the Mean Absolute Percentage Error (MAPE) and Secant Cosine Calculation methods. © 2019 Elsevier B.V. All rights reserved.
Citation - Scopus: 2
Scenario-Based Cellular Automata and Artificial Neural Networks in Urban Growth Modeling
(GAZI UNIV, 2023) Nur Sipahioglu; Gulen Cagdas; Cagdas, Gulen; Sipahioğlu, Nur
The speed at which cities are growing and developing today cannot be disregarded. Human activities and natural causes are both contributors to urban growth. The relationship between these factors is complex and the complexity makes it difficult for the human mind alone to understand cities. A model that helps reveal the complexity is needed for urban studies. Main objective of this study is to understand the effects of urban planning strategies on the future of the city by utilizing a Cellular Automata and Artificial Neural Networks based simulation model. Driving factors of urban growth according to development scenarios were used in the simulation process. Six different development scenarios were formulated according to the strategic plan of Izmir. Land use and driving factor data used in simulating scenarios were acquired from EarthExplorer and OpenStreetMap databases and produced in QGIS. Future Land Use Simulation Model (FLUS) based on Cellular Automata (CA) and Artificial Neural Networks (ANN) was used. The results were assessed both by using FRAGSTATS which helped calculate fractal dimensions and visual analysis. Fractal dimension results of each scenario showed that the simulation model respected the overall urban complexity. A closer look at each scenario indicated the diverse local growth possibilities for different scenarios. The results show that urban simulation models when used as decision support tools promise a more inclusive and explicit planning process.