ResearchBib Share Your Research, Maximize Your Social Impacts
Sign for Notice Everyday Sign up >> Login

Modified Model of Predicting Traffic using KNN and Euclidean Distance

Journal: International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) (Vol.6, No. 5)

Publication Date:

Authors : ;

Page : 127-130

Keywords : ;

Source : Downloadexternal Find it from : Google Scholarexternal

Abstract

Abstract-Adverse situations creep in as traffic enhances on road. This leads to significant problems for users. These problems include delay and accidents. Traffic problem is difficult to address but users can be given prior information about on road traffic so that user can take appropriate action in terms of choosing path. This research paper deals with traffic prediction to predict on road traffic using KNN and Euclidean distance mechanism. The mechanism is implied on dataset derived from online source(UCI). For demonstration three lanes are considered for prediction. Implementation is done within MATLAB. The obtained accuracy of prediction is high and mean square error is low through the proposed literature. Keywords-Accuracy, Euclidean Distance, KNN, Mean Square Error, Prediction, Traffic

Last modified: 2017-11-25 17:54:31