• Dr.S. Krishnaveni
• R.V.Divya

Uber Technologies Inc. is an American international transportation network company headquarter in San Francisco, California and founded as “UberCab” by Travis Kalanick and Garrett Camp in March 2009.It develops, markets and operates the uber mobile app, which allows consumers with smartphones to submit a trip request which is then routed to uber drivers who use their own cars. This paper explores the applications of machine learning for predicting the travel time in the ride sourcing networks using time series modelling in Uber movement dataset. To this end, in the first step, descriptive analytics is completed to include potential features(attributes) affecting the travel times of Uber (ride sourcing) services. Then forecasting techniques such as time series modelling are applied to identify key attributes(features) for the prediction of the average travel times. To predict the accuracy of the average travel times using Time series modelling and Decision tree classifier.

Uber movement, Travel time prediction, Time series modelling, Decision tree classifier.

"PREDICT THE TRAVEL TIME USING TIME SERIES MODELING AND CLASSIFIER ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.289-293, June-2022, Available :http://www.jetir.org/papers/JETIRFN06048.pdf

"PREDICT THE TRAVEL TIME USING TIME SERIES MODELING AND CLASSIFIER ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp289-293, June-2022, Available at : http://www.jetir.org/papers/JETIRFN06048.pdf