Study on Traffic Volume Forecasting of Imperial River Bridge Based on the Theory of Serial Number Summation
Guo Xiao-kui
Abstract
Guo Xiao-kui
Abstract
In order to evaluate the reliability of road network design,improve the accuracy of traffic volume forecasting,with the guidance of basic traffic engineering theory,based on a large number of survey data,the paper conducts traffic volume forecasting using linear,binomial,exponential time series and other methods,obtains the corresponding prediction model,gets prediction model with higher accuracy by means of using the theory of serial number summation,and calculates traffic volume of future characteristic year through prediction,which provides a new research ideas for the study of on traffic volume forecasting.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In order to evaluate the reliability of road network design,improve the accuracy of traffic volume forecasting,with the guidance of basic traffic engineering theory,based on a large number of survey data,the paper conducts traffic volume forecasting using linear,binomial,exponential time series and other methods,obtains the corresponding prediction model,gets prediction model with higher accuracy by means of using the theory of serial number summation,and calculates traffic volume of future characteristic year through prediction,which provides a new research ideas for the study of on traffic volume forecasting.
Key concepts: Traffic volume, Volume (thermodynamics), Reliability (semiconductor), Computer science, Negative binomial distribution, Traffic generation model, Bridge (graph theory), Series (stratigraphy)