Modelling trip distribution with fuzzy and genetic fuzzy systems |
| |
Authors: | Mert Kompil H Murat Celik |
| |
Institution: | 1. European Commission, Joint Research Centre (JRC) , Institute for Prospective Technological Studies (IPTS) , C/ Inca Garcilaso 3, 41092 , Seville , Spain;2. Department of City and Regional Planning , Izmir Institute of Technology , 35430 , Izmir , Turkey Mert.kompil@ec.europa.eu;4. Department of City and Regional Planning , Izmir Institute of Technology , 35430 , Izmir , Turkey |
| |
Abstract: | 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. |
| |
Keywords: | trip distribution spatial interaction models fuzzy logic fuzzy rule-based systems genetic fuzzy systems genetic algorithms neural networks |
|
|