Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to
solve combinatorial optimization problems. In recent years, advances in quantum …

In the last two decades, the growing need for short‐term prediction of traffic parameters
embedded in a real‐time intelligent transportation systems environment has led to the …

Most literature on short-term traffic flow forecasting focused mainly on normal, or non-
incident, conditions and, hence, limited their applicability when traffic flow forecasting is most …

Short-term forecasting of traffic parameters such as flow and occupancy is an essential
element of modern Intelligent Transportation Systems research and practice. Although many …

Traffic congestion causes important problems such as delays, increased fuel consumption
and additional pollution. In this paper we propose a new method to optimize traffic flow …

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership
estimates that account for day-to-day demand variations in the near future (eg, next week …

A radial basis function (RBF) neural network has recently been applied to time-series
forecasting. The test results of an RBF neural network in forecasting short-term freeway …

In peak hours, when the limited transportation capacity of urban rail transit is not adequate
enough to meet the travel demands, the density of the passengers waiting at the platform …

This paper presents an adaptive hybrid fuzzy rule-based system (FRBS) approach for the
modeling and short-term forecasting of traffic flow in urban arterial networks. Such an …

Current interest in short‐term traffic volume forecasting focuses on incorporating temporal
and spatial volume characteristics in the forecasting process. This article addresses the …