This project implements a real-time dynamic pricing model for urban parking lots using advanced data analytics. It leverages live and historical data to automatically adjust parking fees based on multiple parameters such as demand, occupancy levels, time of day, location, and nearby events.
Neural network using cross entropy loss for price calculations on cinema dynamic pricing system.
A Dynamic Pricing framework integrating Monte Carlo simulations for demand uncertainty analysis and Response Surface Methodology (RSM) to optimize pricing strategies and maximize revenue.
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