scholarly journals Traffic Flow Prediction Based on Local Mean Decomposition and Big Data Analysis

2019 ◽  
Vol 24 (5) ◽  
pp. 547-552 ◽  
Author(s):  
Wei Liu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Traffic Flow ◽  
Big Data Analysis ◽  
Local Mean Decomposition ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Local Mean

Big data‐driven machine learning‐enabled traffic flow prediction

2018 ◽  
Vol 30 (9) ◽  
Author(s):  
Fanhui Kong ◽  
Jian Li ◽  
Bin Jiang ◽  
Tianyuan Zhang ◽  
Houbing Song
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Traffic Flow ◽  
Data Driven ◽  
Traffic Flow Prediction ◽  
Flow Prediction

scholarly journals When Traffic Flow Prediction and Wireless Big Data Analytics Meet

IEEE Network ◽  
2019 ◽  
Vol 33 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Yuanfang Chen ◽  
Mohsen Guizani ◽  
Yan Zhang ◽  
Lei Wang ◽  
Noel Crespi ◽  
...  
Keyword(s):  
Big Data ◽  
Traffic Flow ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Wireless Big Data

Dynamic spatial-temporal feature optimization with ERI big data for Short-term traffic flow prediction

2020 ◽  
Vol 412 ◽  
pp. 339-350
Author(s):  
Linjiang Zheng ◽  
Jie Yang ◽  
Li Chen ◽  
Dihua Sun ◽  
Weining Liu
Keyword(s):  
Big Data ◽  
Traffic Flow ◽  
Short Term ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Feature Optimization ◽  
Temporal Feature

Forecasting Website Traffic Using Prophet Time Series Model

2019 ◽  
Vol 1 (1) ◽  
pp. 56-63
Author(s):  
A Subashini ◽  
Sandhiya K ◽  
S Saranya ◽  
U Harsha
Keyword(s):  
Time Series ◽  
Big Data ◽  
Traffic Flow ◽  
Prediction Models ◽  
Internet Traffic ◽  
Time Series Model ◽  
Traffic Data ◽  
Traffic Flow Prediction ◽  
Flow Monitoring ◽  
Flow Prediction

Web traffic is the amount of data sent and received by visitors to a website and it has been the largest portion of Internet traffic. Internet traffic flow prediction heavily depends on historical and real-time traffic data collected from various internet flow monitoring sources. With the widespread traditional traffic sensors and new emerging traffic sensor technologies, traffic data are exploding, and we have entered the era of big data internet traffic. Internet traffic management and control driven by big data is becoming a new trend. Although there have been already many internet traffic flow prediction systems and models, most of which use shallow traffic models and are still somewhat unsatisfying. This inspires us to reconsider the internet traffic flow prediction model based on deep architecture models with such rich amount of internet traffic data. ARIMA is a existing forecasting technique that predicts the future values of a series based entirely on its own inertia. Existing traffic flow prediction methods mainly use simple traffic prediction models and are still unsatisfying for many real-world applications. Now we proposed the prophet time series model to forecasting website traffic.

Sign in / Sign up

Export Citation Format

Share Document