منابع مشابه
A GMDH-Based Traffic Flow Forecasting Model
Traffic flow forecasting, the core element of intelligent transportation system, plays an important role in traffic information services and traffic guidance. Since neural network prediction needs plenty of training samples, it cannot guarantee the real-timeness of traffic flow forecasting. In this paper, a GMDH network was constructed by self-organization, and the network was applied to traffi...
متن کاملAn Aggregate Sector Flow Model for Air Traffic Demand Forecasting
Sector capacity, number of aircraft permitted in a region of the airspace referred to as a sector, is used to limit air traffic to an amount that can be safely handled by a human controller. The traditional approach for predicting traffic demand in a sector involves the simulation of trajectories of individual aircraft. The demand provided by this approach is inaccurate for hourly time horizons...
متن کاملmortality forecasting based on lee-carter model
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
15 صفحه اولTraffic Flow Forecasting Using a Spatio-temporal Bayesian Network Predictor
A novel predictor for traffic flow forecasting, namely spatiotemporal Bayesian network predictor, is proposed. Unlike existing methods, our approach incorporates all the spatial and temporal information available in a transportation network to carry our traffic flow forecasting of the current site. The Pearson correlation coefficient is adopted to rank the input variables (traffic flows) for pr...
متن کاملTime-Series Modeling For Forecasting Vehicular Traffic Flow in Dublin
The traffic flow at an arterial intersection in a congested urban transportation network in the city of Dublin is modelled in this paper. Three different time-series models, viz. random walk model, Holt-Winters’ exponential smoothing technique and seasonal ARIMA model are used for modeling of traffic flow in Dublin. Simulation and short-term forecasting of univariate traffic flow data are done ...
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ژورنال
عنوان ژورنال: Lietuvos matematikos rinkinys
سال: 2012
ISSN: 2335-898X,0132-2818
DOI: 10.15388/lmr.b.2012.45