Origin-based algorithms for combined travel forecasting models
نویسندگان
چکیده
Consistent transportation forecasting models that combine travel demand and network assignment are receiving more attention in recent years. A fixed point formulation for the general combined model is presented. Measures for solution accuracy are discussed. An origin-based algorithm for solving combined models is proposed. Experimental results demonstrate the efficiency of the algorithm in comparison with prevailing alternatives. 2003 Elsevier Science Ltd. All rights reserved.
منابع مشابه
Validation of Multiclass Urban Travel Forecasting Models Combining Origin- Destination, Mode, and Route Choices*
The formulation, estimation, and validation of combined models for making detailed urban travel forecasts are described. These models combine origin-destination, mode, and auto route choices into a consistent forecasting method for multiple user classes for the Chicago Region. Household Travel Survey and Census Transportation Planning Package data for 1990, respectively, are used to estimate an...
متن کاملMulticlass Combined Models for Urban Travel Forecasting
Progress in formulating, solving and implementing models with multiple user classes that combine several travel choices into a single, consistent mathematical formulation is reviewed. Models in which the travel times and costs on the road network are link flow-dependent are considered; such models seek to represent congestion endogenously. The paper briefly summarizes the origins of this field ...
متن کاملSupernetworks for Combined Travel Choice Models
A supernetwork is usually defined as an augmented network that consists of a “basic network” for route choice and a “virtual network” for other travel choices. Supernetwork representations are useful pedagogical device to interpret various combined travel choice models as an extension of the fixed demand traffic assignment problem. Based on three proposed criteria, this paper reviews current su...
متن کاملA Review of Epidemic Forecasting Using Artificial Neural Networks
Background and aims: Since accurate forecasts help inform decisions for preventive health-careintervention and epidemic control, this goal can only be achieved by making use of appropriatetechniques and methodologies. As much as forecast precision is important, methods and modelselection procedures are critical to forecast precision. This study aimed at providing an overview o...
متن کاملModeling and forecasting US presidential election using learning algorithms
The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are co...
متن کامل