5 citations · 23 across the 17 of their papers we have counts for
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Predicting Short-Term Uber Demand Using Spatio-Temporal Modeling: A New York City Case Study
Sabiheh Sadat Faghih, Abolfazl Safikhani, Bahman Moghimi +1
The demand for e-hailing services is growing rapidly, especially in large cities. Uber is the first and popular e-hailing company in the United Stated and New York City. A comparis…
Short-Term Prediction of Signal Cycle in Actuated-Controlled Corridor Using Sparse Time Series Models
Bahman Moghimi, Abolfazl Safikhani, Camille Kamga +2
Traffic signals as part of intelligent transportation systems can play a significant role toward making cities smart. Conventionally, most traffic lights are designed with fixed-ti…
Spatio-temporal Modeling of Yellow Taxi Demands in New York City Using Generalized STAR Models
Abolfazl Safikhani, Camille Kamga, Sandeep Mudigonda +2
A highly dynamic urban space in a metropolis such as New York City, the spatio-temporal variation in demand for transportation, particularly taxis, is impacted by various factors s…
Joint Structural Break Detection and Parameter Estimation in High-Dimensional Non-Stationary VAR Models
Abolfazl Safikhani, Ali Shojaie
Assuming stationarity is unrealistic in many time series applications. A more realistic alternative is to allow for piecewise stationarity, where the model is allowed to change at…
Structural Break Detection in High-Dimensional Non-Stationary VAR models
Abolfazl Safikhani, Ali Shojaie
Assuming stationarity is unrealistic in many time series applications. A more realistic alternative is to allow for piecewise stationarity, where the model is allowed to change at…