Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous
studies have focused on TMC in adults, whereas predicting TMC in children has received …

Forecast of air transport demand has a great influence on the development of airport master
plans with respect both to airside (runways, taxiways, aprons, technological devices) and …

This study aims to investigate the feasibility of using the Adaptive Neuro-Fuzzy Inference
System (ANFIS) and Multiple Linear Regression (MLR) for modelling home-based trip …

Air demand forecast at airports is an important problem for the airport management and also
for the regulator that has to plan a homogeneous development of the overall transport …

Since the last two decades, several modeling approaches have been developed in road
safety literature to establish the relationship between traffic accidents and road …

Queue management is a valuable but underutilized technique which could be used to
minimize the negative impacts of queues during oversaturated traffic conditions. One of the …

Increasing congestion on the main roads in urban areas pushes analysts to improve
simulation of modal choice to obtain good estimation of the demand shares for different …

Abstract The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used in this study to model
the non-linear relationship between intercity train service quality (SQ) and its attributes …

This study applies probabilistic neural network (PNN) and adaptive neuro fuzzy inference
system (ANFIS) to develop bus service quality (SQ) prediction model based on the …

Development of trip generation models has been conducted mainly using the traditional
Multiple Linear Regression approach, which sometimes might not necessarily result in …