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A stepwise interpretable machine learning framework using linear regression (LR) and long short-term memory (LSTM): City-wide demand-side prediction of yellow taxi and for-hire vehicle (FHV) service

Taehooie Kim, Shivam Sharda, Xuesong Zhou, Ram M. Pendyala

2020Transportation Research Part C Emerging Technologies83 citationsDOI

Topics & Concepts

TaxisComputer scienceArtificial neural networkService (business)Demand forecastingArtificial intelligenceDeep learningOrder (exchange)Term (time)Machine learningOperations researchTransport engineeringEngineeringBusinessMarketingPhysicsQuantum mechanicsFinanceTransportation and Mobility InnovationsTransportation Planning and OptimizationTraffic Prediction and Management Techniques
A stepwise interpretable machine learning framework using linear regression (LR) and long short-term memory (LSTM): City-wide demand-side prediction of yellow taxi and for-hire vehicle (FHV) service | Litcius