stdClass Object
(
    [id] => 15443
    [paper_index] => 202503-01-020759
    [title] => SUPERVISED LEARNING-BASED RIDE FARE PREDICTION
    [description] => 
    [author] => Akhilash Pennam, Pavan Kumar Potula
    [googlescholar] => 
    [doi] => https://doi.org/10.36713/epra20759
    [year] => 2025
    [month] => March
    [volume] => 11
    [issue] => 3
    [file] => fm/jpanel/upload/2025/March/202503-01-020759.pdf
    [abstract] => One of the most well-known ride-sharing services worldwide is Uber. This Uber price prediction system will precisely forecast the cost of a ride by combining machine learning algorithms with past data in order to give clients the best service possible. Taxi services are currently the most popular means of transportation. Rapid change has occurred in corporations, and they are now moving toward digital innovation. Historically, software companies and product developers have developed a number of methods, but they haven't considered the necessity of a customer's mobility in a certain location. In order to develop a precise model for forecasting future pricing, the Uber price prediction system will examine historical trip data, traffic, weather, time of day, and other pertinent information. To produce its predictions, it will employ a range of methods including linear regression.
    [keywords] => Uber, Supervised Machine Learning, Business, Price Prediction.
    [doj] => 2025-03-31
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 108
    [journal_id] => 1
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Multidisciplinary Research (IJMR)
    [short_code] => IJMR
    [eissn] =>  2455-3662 (Online)
    [pissn] => - --
    [home_page_wrapper] => images/products_image/11.IJMR.png
)
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