Traffic information estimation and forecasting methods based on cellular floating vehicle data (CFVD) are proposed to analyze the signals (e.g., handovers (HOs), call arrivals (CAs), normal location updates (NLUs) and periodic location updates (PLUs)) from cellular networks. For traffic information estimation, analytic models are proposed to estimate the traffic flow in accordance with the amou...

-The analytical study and forecasting of network traffic has wide applications in many areas of technology and has led to many researches in the current field. Various experiments and analysis has been carried out in the field of computer network applications. The analysis and forecasting of network traffic is a means of reliable and secure network communication. Many techniques have been propo...

In order to forecast mobile communication traffic quickly and accurately, Hidden Markov Models (HMM) is used to forecast busy hour traffic of wireless mobile communication forecasting in this paper. Because of the model having rigorous mathematical structure, reliable computing performance and the characteristics of describing the event, HMM becomes the ideal model for describing the traffic se...

I nrecent years there has been a noticeable shift away from the application of computer-based transportation modeling methods in smallto medium-sized urban areas. In many cases, this shift has resulted from a disenchantment with the complex modeling methodologies used in the late 1960s and early 1970s. The expense of such methods, in terms of data collection and computational costs, was simply ...

Traffic forecasting has recently become a crucial task in the area of intelligent transportation systems, and in particular in the development of traffic management and control. We focus on the simultaneous prediction of the congestion state at multiple lead times and at multiple nodes of a transport network, given historical and recent information. This is a highly relational task along the sp...

Analysis and short-term forecasting of traffic flow data for several locations of the Slovenia highway network are presented. Daily and weekly seasonal components of the data are analysed and several features are extracted to support the forecasting. Various short-term forecasting models are developed for one hour ahead forecasting of the traffic flow. Models include benchmark models (random wa...

In this paper, different modeling philosophies are explored in order to explain and forecast daily traffic counts. The main objectives of this study are the analysis of the impact of holidays on daily traffic, and the forecasting of future traffic counts. Data coming from single inductive loop detectors, collected in 2003, 2004 and 2005, were used for the analysis. The different models that wer...

Internet traffic forecasting models with learning ability, such as the artificial neural network (ANN), have been growing in popularity in recent time due to their impressive performance in modelling the high degree of variability and nonlinearity of internet traffic. This study examined the impacts of some design issues on performance of the multi-layer artificial neural network for internet t...