Ensemble forecasting is a modeling approach that combines data sources, models of
different types, with alternative assumptions, using distinct pattern recognition methods. The …

This paper provides a review of transport model applications that not only provide a central
traffic forecast (or forecasts for a few scenarios), but also quantify the uncertainty in the traffic …

This article presents results from the first statistically significant study of traffic forecasts in
transportation infrastructure projects. The sample used is the largest of its kind, covering 210 …

In this paper, we propose a new model called the α-reliable mean-excess traffic equilibrium
(METE) model that explicitly considers both reliability and unreliability aspects of travel time …

This paper proposes a novel traffic assignment model considering uncertainties in both
demand and supply sides of a road network. These uncertainties are mainly due to adverse …

Origin-Destination (OD) travel demand prediction is a fundamental challenge in
transportation. Recently, spatial-temporal deep learning models demonstrate the …

Public transport was already one of the biggest issues for all municipalities where people
are highly concentrated at the same space at the same time. With COVID-19 pandemic and …

Aiming to develop a theoretically consistent framework to estimate travel demand using
multiple data sources, this paper first proposes a multi-layered Hierarchical Flow Network …

Harmful algal blooms frequently occur globally, and forecasting could constitute an essential
proactive strategy for bloom control. To decrease the cost of aquatic environmental …

Remote sensing reflectance (Rrs) values measured by satellite sensors involve large
amounts of uncertainty leading to non-negligible noise in remote Chlorophyll-a (Chl-a) …