City and Regional Planning / Şehir ve Bölge Planlama
Permanent URI for this collectionhttps://hdl.handle.net/11147/4274
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Research Project İmar afları sonrasında İzmir'de gecekondulaşma: Sosyo-ekonomik, mekansal bir çözümleme(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2005) Özdemir, Semahat; Arslan Avar, Adile; Şenol, Pervin; Sevinç Kaya, Nuray; Kutluca, Ahmet Kıvanç; Velibeyoğlu, Hasibe; Güçer, Evrim; Kompil, Mert; Yankaya, Uğur; Elvan, İrem; Bektaş, Birkan; İnce Kompil, Esin[No Abstract Available]Book Part Citation - WoS: 2Modelling and Projecting Urban Land Cover(Routledge, 2017) Lavalle, Carlo; Batista e Silva, Filipe; Baranzelli, Claudia; Jacobs-Crisioni, Chris; Barbosa, Ana Luisa; Aurambout, Jean-Philippe; Vizcaino, Pilar; Kompil, Mert[No abstract available]Article Citation - WoS: 9Citation - Scopus: 10Modelling Trip Distribution With Fuzzy and Genetic Fuzzy Systems(Taylor and Francis Ltd., 2013) Kompil, Mert; Çelik, Hüseyin MuratThis paper explores the potential capabilities of fuzzy and genetic fuzzy system approaches in urban trip distribution modelling with some new features. First, a simple fuzzy rule-based system (FRBS) and a novel genetic fuzzy rule-based system [GFRBS: a fuzzy system improved by a knowledge base learning process with genetic algorithms (GAs)] are designed to model intra-city passenger flows for Istanbul. Subsequently, their accuracy, applicability and generalizability characteristics are evaluated against the well-known gravity- and neural network (NN)-based trip distribution models. The overall results show that: traditional doubly constrained gravity models are still simple and efficient; NNs may not show expected performance when they are forced to satisfy trip constraints; simply-designed FRBSs, learning from observations and expertise, are both efficient and interpretable even if the data are large and noisy; and use of GAs in fuzzy rule-based learning considerably increases modelling performance, although it brings additional computation cost.