Based on a large database from a real bus system, this paper aims to present a passenger demand prediction system for mobile users.
Zhou, C., Dai, P., Wang, F. and Zhang, Z. (2016) Predicting the Passenger Demand on Bus Services for Mobile Users. Pervasive and Mobile Computing, 25, 48-66.
There are three major challenges for predicting the passenger demand on bus services: inhomogeneous, seasonal bursty periods and periodicities. To overcome the ...
This work proposes three predictive models and takes a data stream ensemble framework to predict the number of passengers and demonstrates that the approach ...
Abstract. This article investigated machine learning models used to estimate passenger demand. These models have the potential to provide valuable insights ...
In this paper we present the passenger demand prediction model of BusGrid. BusGrid is a novel information system for the improvement of productivity and ...
Oct 8, 2015 · However, there are three major challenges for predicting the passenger demand on bus services: inhomogeneous, seasonal bursty periods and ...
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The invention discloses a bus-network-based system and method for predicting passenger requirements. According to the method, the unevenness, the abruptness ...
Apr 23, 2024 · A prediction model with LSTM based on deep learning is proposed to predict passengers for 4 bus public transportation operators (Go Bus, New Zealand Bus, ...
Aug 9, 2024 · By comparing the resident travel flow OD with the bus passenger flow OD, we set a threshold for the potential bus passenger demand proportion.