NDLI: Short-term Traffic Flow Forecasting Based on ARIMA-ANN

Content Provider	IEEE Xplore Digital Library
Author	Huang hong-qiong Tang tian-hao
Copyright Year	2007
Description	Author affiliation: Shanghai Maritime Univ., Shanghai (Huang hong-qiong; Tang tian-hao)
Abstract	ARIMA and ANN are very practical forecasting technology in short-term traffic flow forecasting fields. Both ARIMA and ANN have different characteristics. ARIMA is suitable for linear prediction and ANN is suitable for nonlinear prediction. Because of the complexity of the historical traffic data and the randomness of a lot of uncertain factors influence, the observed data include the linear and nonlinear parts. The choice of the forecasting model becomes the important influence factor how to improve forecasting accuracy. A combined model of ARIMA-ANN is proposed in the text. The linear part of the historical load data can be dealt with ARIMA, and ANN model can deal with the nonlinear part of historical load data. Empirical results indicate that a hybrid ARIMA-ANN model can improve the forecasting accuracy.
Starting Page	2370
Ending Page	2373
File Size	413617
Page Count	4
File Format	PDF
ISBN	9781424408177
DOI	10.1109/ICCA.2007.4376785
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Autoregressive processes Traffic control Predictive models Artificial neural networks Educational institutions Telecommunication traffic Neural networks Stochastic processes Intelligent transportation systems Automatic control Short-term Traffic flow forecasting Time series ARIMA model ANN model
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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