Modelling trip distribution with fuzzy and genetic fuzzy systems

作者：Kompil Mert^*; Celik H Murat

来源：Transportation Planning and Technology, 2013, 36(2): 170-200.

DOI：10.1080/03081060.2013.770946

• trip distribution
• spatial interaction models
• fuzzy logic
• fuzzy rule-based systems
• genetic fuzzy systems
• genetic algorithms
• neural networks

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.

• 出版日期2013-3-1