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Modern Transportation

Modern Transportation (half-yearly) is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of transportation building and management. The main focus of the journal is the academic papers and comments of latest transportation engineering, system engineering and road engineering improvement in the fields of nature science, engineering technology, economy and science, report of latest research re... [More] Modern Transportation (half-yearly) is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of transportation building and management. The main focus of the journal is the academic papers and comments of latest transportation engineering, system engineering and road engineering improvement in the fields of nature science, engineering technology, economy and science, report of latest research result, aiming at providing a good communication platform to transfer, share and discuss the theoretical and technical development for professionals, scholars and researchers in this field, reflecting the academic front level, promote academic change and seize the transportation technology theory, practice front line, research level and development direction.

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ISSN Print:2327-0713

ISSN Online:2327-1027

Email:mt@ivypub.org

Website: http://www.ivypub.org/mt/

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Paper Infomation

Forecast of Short-term Traffic Flow in Chengdu City Based on Decision Tree Model

Full Text(PDF, 705KB)

Author: Jingdian Yang

Abstract: With the rapid increase in the population in the central area of Chengdu, congestion in a certain period has become one of the stubborn diseases that restrict the development of the city. By accurately predicting the short-term road traffic information in the future, it can effectively improve the traffic efficiency of vehicles in a specific period. In this paper, data training is carried out according to the collected relevant indicators, and a decision tree classification model is established. The model can be used to predict the traffic flow on the road in a short period of time based on the time of the road, weather, average speed, and other indicators, and then the relevant regulatory authorities can use the advanced new media today to push, so that the citizens can plan their trips reasonably.

Keywords: Traffic Jam, Machine Learning, Decision Tree, Prediction

References:

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[4] 刘张,李坚,王超,蔡世民,唐明,黄琦,陈照辉. 基于复杂城市道路网络的交通拥堵预测模型[j]. 电子科技大学学报. 2016,45(01).

[5] 支野,王大珊,丛浩哲,饶众博. 道路交通事故数据深度挖掘技术与应用——以深圳市为例[j]. 城市交通. 2018,16(03).

[6] 薛红军,陈广交,李鑫民,顾理.基于决策树理论的交通流参数短时预测[j].交通信息与安全,2016,34(03).

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