Over a period of time the volume of network traffic generated by an Internet application is equal to the cumulative size of the packets that carried the traffic. We propose a method of estimating the expected volume of network traffic that will be generated by a population of WorldWide Web users based on estimating the cumulative size of the expected hypertext transfer protocol (HTTP) packets. ...

This paper considers the problem of estimating the yearly traffic volume at a count site, when traffic counts are available for only a limited part of the year, perhaps only a few hours or days. A new method for estimating annual average daily traffic (AADT) based on regression is presented. In addition to being more precise than the traditional factor approach, the new method supplies the prec...

9 Traffic speed and length-based vehicle classification data are critical inputs for traffic operations, 10 pavement design and maintenance, and transportation planning. However, they cannot be 11 measured directly by single-loop detectors, the most widely deployed type of traffic sensor in the 12 existing roadway infrastructure. In this study, a Gaussian Mixture Model (GMM)-based 13 approach i...

The existing well-known short-term traffic forecasting algorithms require large traffic flow data sets, including information on current traffic scenarios to predict the future traffic conditions. This article proposes a random process traffic volume model that enables estimation and prediction of traffic volume at sites where such large and continuous data sets of traffic condition related inf...

objective the hippocampal circuit integrity is crucial for learning and memory. despite the existing reports on hippocampal–dependent memory impairment due to noise stress, there are only a few studies on the effect of noise stress on anatomical structure of hippocampus. the present study is aimed to investigate the likely effects of chronic noise exposure on the volume of rat hippocampus. mate...

In street-based mobility mining, traffic volume estimation receives increasing attention as it provides important applications such as emergency support systems, quality-of-service evaluation and billboard placement. In many real world scenarios, empirical measurements are usually sparse due to some constraints. On the other hand, pedestrians generally show some movement preferences, especially...

Background and Aim: High concentrations of particulate matter-25 (PM2.5) have been the cause of the unhealthiest days in Tehran, Iran in recent years. This study was conducted with the aim of the spatio-temporal analysis of traffic volume and its relationship with PM2.5 pollutant concentrations in Tehran metropolis, Tehran during 2015-2018, using the Geographic Information System (GIS). Materi...

Road traffic volumes in intercity roads are generally estimated by probability functions, statistical techniques or meta-heuristic approaches such as artificial neural networks. As the road traffic volumes depend on input variables and mainly road geometrical design, weather conditions, day or night time, weekend or national holidays and so on, these are also estimated by pattern recognition te...

D ifferent types of volume counting programs are undertaken by state and local roadway agencies to obtain values of traffic parameters such as average annual daily traffic (AADT). Some of the commonly used traffic counts in areawide volume studies include: continuous counts by automatic traffic recorders (ATR) in which volume is recorded 24 hours each day, 365 days a year; seasonal counts in wh...