Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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2004 - 200912010 - 20131

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Subject: search.filters.subject.Spatial interaction modelsWoS Q: search.filters.wosQuartile.Q3

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  • Article
    Citation - WoS: 9
    Citation - Scopus: 10
    Modelling Trip Distribution With Fuzzy and Genetic Fuzzy Systems
    (Taylor and Francis Ltd., 2013) Kompil, Mert; Çelik, Hüseyin Murat
    This 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.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 8
    Forecasting Interregional Commodity Flows Using Artificial Neural Networks: an Evaluation
    (Taylor and Francis Ltd., 2004) Çelik, Hüseyin Murat
    Previous studies have concluded that the use of artificial neural networks (ANNs) is a promising new technique for modelling freight distribution, supporting, the findings of other studies in the area of spatial interaction modelling. However, the forecasting performance of ANNs is still under investigation. This study tests the predictive performance of the ANN Model with respect to a Box-Cox spatial interaction model. It is concluded that the Box-Cox model outperforms ANN in forecasting interregional commodity flows even if ANN had proven calibration superiority in comparison to conventional gravity type models.