NEURO-FUZZY AND ROUGH SET BASED TRAFFIC FLOW PREDICTION

ICTACT Journal on Soft Computing ( Volume: 10 , Issue: 3 )

Abstract

vioft2nntf2t|tblJournal|Abstract_paper|0xf4ffad662b000000b9b0050001000600
With the rapid growth in urban population and vehicle ownership, traffic congestion has become a severe problem everywhere in the world and is only expected to rise. This problem can be avoided by knowing the traffic situation in advance which is achieved with the help of traffic flow prediction. In the proposed work, traffic flow is predicted on short term basis using neuro-fuzzy hybrid system in combination with rough set. The neuro-fuzzy hybrid system combines the complementary capabilities of both neural networks and fuzzy logic. The work has attempted to study the effect of aggregation intervals and past samples on the prediction performance using MSE threshold variation. Rough set is used as a post processing tool. The objective is to improve prediction accuracy. Data from highway of Chennai, India is used for the analysis. It is found that use of rough set results in considerable improvement in the prediction performance as indicated by performance measures like MSE, RMSE etc.

Authors

Minal Deshpande
GH Raisoni College of Engineering, India

Keywords

Intelligent Transportation Systems (ITS), Rough Set Theory (RST), Short Term Traffic Flow Prediction, Neuro-fuzzy Hybrid System

Published By
ICTACT
Published In
ICTACT Journal on Soft Computing
( Volume: 10 , Issue: 3 )
Date of Publication
April 2020
Pages
2102-2106

ICT Academy is an initiative of the Government of India in collaboration with the state Governments and Industries. ICT Academy is a not-for-profit society, the first of its kind pioneer venture under the Public-Private-Partnership (PPP) model

Contact Us

ICT Academy
Module No E6 -03, 6th floor Block - E
IIT Madras Research Park
Kanagam Road, Taramani,
Chennai 600 113,
Tamil Nadu, India

For Journal Subscription: journalsales@ictacademy.in

For further Queries and Assistance, write to us at: ictacademy.journal@ictacademy.in