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Network performance model for urban rail systems
(Massachusetts Institute of Technology, 2020)
Urban rail transit is an important component of transportation systems and plays a critical role in providing smooth and efficient mobility in many metropolitan areas. Network performance monitoring, i.e. assessing the ...
Learning structure in nested logit models
(Massachusetts Institute of Technology, 2019)
This work is about developing an estimation procedure for nested logit models that optimizes over the nesting structure in addition to the model parameters. Current estimation practices require an a priori specification ...
Constrained extended Kalman filter : an efficient improvement of calibration for dynamic traffic assignment models
(Massachusetts Institute of Technology, 2016)
The calibration (estimation of inputs and parameters) for dynamic traffic assignment (DTA) systems is a crucial process for traffic prediction accuracy, and thus critical to global traffic management applications to reduce ...
Urban computing using call detail records : mobility pattern mining, next-location prediction and location recommendation
(Massachusetts Institute of Technology, 2016)
Urban computing fuses computer science with other fields, such as transportation, in the context of urban spaces by connecting ubiquitous sensing technologies, analytical models and visualizations to solve challenging ...
Optimization of yard operations in maritime container terminals
(Massachusetts Institute of Technology, 2015)
With the continuous growth in international container shipping, many container terminals in maritime ports face congestion, particularly during peak hours of service, and when there is limited space in the storage area. ...
Near-optimal data-driven approximation schemes for joint pricing and inventory control models
(Massachusetts Institute of Technology, 2018)
The thesis studies the classical multi-period joint pricing and inventory control problem in a data-driven setting. In the problem, a retailer makes periodic decisions of the prices and inventory levels of an item that the ...
Analytics for hotels : demand prediction and decision optimization
(Massachusetts Institute of Technology, 2017)
The thesis presents the work with a hotel company, as an example of how machine learning techniques can be applied to improve demand predictions and help a hotel property to make better decisions on its pricing and capacity ...
Predicting and improving invoice-to-cash collection through machine learning/
(Massachusetts Institute of Technology, 2015)
Delinquent invoice payments can be a source of financial instability if it is poorly managed. Research in supply chain finance shows that effective invoice collection is positively correlated with the overall financial ...
Machine learning for real-time demand forecasting
(Massachusetts Institute of Technology, 2015)
For a taxi company, the capability to forecast taxi demand distribution in advance provides valuable decision supports. This thesis studies real-time forecasting system of spatiotemporal taxi demand based on machine learning ...
W-SPSA : an Efficient Stochastic Approximation Algorithm for the off-line calibration of Dynamic Traffic Assignment models
(Massachusetts Institute of Technology, 2014)
The off-line calibration is a crucial step for the successful application of Dynamic Traffic Assignment (DTA) models in transportation planning and real time traffic management. While traditional approaches focus on the ...