A comprehensive review of shared mobility for sustainable transportation systems
This study provides a comprehensive review of the significant elements in sustainable
transportation systems with shared mobility. The main subsets of shared mobility includes …
transportation systems with shared mobility. The main subsets of shared mobility includes …
A novel perspective on travel demand prediction considering natural environmental and socioeconomic factors
Predicting urban travel demand is important in perceiving the future state of a city, deploying
public transportation resources, and building intelligent cities. Influenced by multifarious …
public transportation resources, and building intelligent cities. Influenced by multifarious …
A systematic literature review on machine learning in shared mobility
J Teusch, JN Gremmel, C Koetsier… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Shared mobility has emerged as a sustainable alternative to both private transportation and
traditional public transport, promising to reduce the number of private vehicles on roads …
traditional public transport, promising to reduce the number of private vehicles on roads …
A novel forecasting based scheduling method for household energy management system based on deep reinforcement learning
The demand response (DR) strategy enables household users to actively optimize and
dispatch the household energy management system (HEMS), which may significantly …
dispatch the household energy management system (HEMS), which may significantly …
Spatial variation of ridesplitting adoption rate in Chicago
Ridesplitting, a form of ride-hailing service where passengers with similar travel routes are
matched to the same driver, can reduce the negative effects of solo ride-hailing trips and …
matched to the same driver, can reduce the negative effects of solo ride-hailing trips and …
Forecasting the daily natural gas consumption with an accurate white-box model
Compared with artificial intelligence black-box models, statistical white-box models have
less application and lower accuracy in forecasting daily natural gas consumption that …
less application and lower accuracy in forecasting daily natural gas consumption that …
Multi-layer perceptron based transfer passenger flow prediction in Istanbul transportation system
Estimating passenger movement in transportation networks is a critical aspect of public
transportation systems. It allows for a greater understanding of traffic patterns, as well as …
transportation systems. It allows for a greater understanding of traffic patterns, as well as …
[PDF][PDF] Machine learning approach for spatial modeling of ridesourcing demand
Accurately forecasting ridesourcing demand is important for effective transportation planning
and policy-making. With the rise of Artificial Intelligence (AI), researchers have started to …
and policy-making. With the rise of Artificial Intelligence (AI), researchers have started to …
PM2. 5 concentration forecasting through a novel multi-scale ensemble learning approach considering intercity synergy
Accurate PM 2.5 concentration prediction can provide reliable air pollution warning
information to the public. However, previous studies have often focused on the data of the …
information to the public. However, previous studies have often focused on the data of the …
A parallel grid-search-based SVM optimization algorithm on Spark for passenger hotspot prediction
Predicting passenger hotspots helps drivers quickly pick up travelers, reduces cruise
expenses, and maximizes revenue per unit time in intelligent transportation systems. To …
expenses, and maximizes revenue per unit time in intelligent transportation systems. To …