Predicting the price of taxicabs using Artificial Intelligence: A hybrid approach based on clustering and ordinal regression models
Authors:
- Bhawana RathoreBRBhawana Rathore
- Pooja SenguptaPSPooja Sengupta
- Baidyanath BiswasBBBaidyanath Biswas
- Ajay KumarAKAjay Kumar
Open Access
- 18 April 2024
- journal article
- research article
- Published by Elsevier in Transportation Research Part E: Logistics and Transportation Review
- Vol. 185
Abstract
No abstract availableKeywords
This publication has 67 references indexed in Scilit:
- How machine learning informs ride-hailing services: A surveyCommunications in Transportation Research, 2022
- On-demand ride-hailing platforms in competition with the taxi industry: Pricing strategies and government supervisionInternational Journal of Production Economics, 2022
- Machine Learning and feature engineering-based study into sarcasm and irony classification with application to cyberbullying detectionInformation Processing & Management, 2021
- Regulation strategies of ride-hailing market in China: an evolutionary game theoretic perspectiveElectronic Commerce Research, 2020
- Optimal pricing for ride-sourcing platformsEuropean Journal of Operational Research, 2019
- Taxi Service Pricing Based on Online Machine Learning2019
- The order effect on online review helpfulness: A social influence perspectiveDecision Support Systems, 2017
- Genie: A new, fast, and outlier-resistant hierarchical clustering algorithmInformation Sciences, 2016
- Spatial variation of the urban taxi ridership using GPS dataApplied Geography, 2015
- Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approachDecision Support Systems, 2011