UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 11 Issue 1
January-2024
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2401576


Registration ID:
531721

Page Number

f629-f632

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Title

TRAFFIC FLOW FORECAST USING TIME SERIES ANALYSIS

Abstract

Traffic congestion is a thorny issue to many large and medium-sized cities, posing a serious threat to sustainable urban development. Recently,intelligent traffic system (ITS) has emerged as an effective tool to mitigate urban congestion. The key to the ITS lies in the accurate forecast of traffic flow. However, the existing forecast methods of traffic flow cannot adapt to the stochasticity and sheer length of traffic flow time series. To solve the problem, this paper relies on deep learning (DL) to forecast traffic flow through time series analysis. The authors developed a traffic flow forecast model based on the long shortterm memory (LSTM) network. The proposed model was compared with two classic forecast models, namely, the autoregressive integrated moving average (ARIMA) model and the backpropagation neural network (BPNN) model, through long-term traffic flow forecast experiments, using an actual traffic flow time series from OpenITS. The experimental results show that the proposed LSTM network outperformed the classic models in prediction accuracy. Our research discloses the dynamic evolution law of traffic flow, and facilitates the decision-making of traffic management.

Key Words

Deep Learning, Long Short Term Memory Networks (LSTM), Training set, Test set, Tensorflow, Traffic Flow Prediction.

Cite This Article

"TRAFFIC FLOW FORECAST USING TIME SERIES ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 1, page no.f629-f632, January-2024, Available :http://www.jetir.org/papers/JETIR2401576.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"TRAFFIC FLOW FORECAST USING TIME SERIES ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 1, page no. ppf629-f632, January-2024, Available at : http://www.jetir.org/papers/JETIR2401576.pdf

Publication Details

Published Paper ID: JETIR2401576
Registration ID: 531721
Published In: Volume 11 | Issue 1 | Year January-2024
DOI (Digital Object Identifier):
Page No: f629-f632
Country: Hyderabad, Telangana, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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