Optimization of spatial-temporal graph: A taxi demand forecasting model based on spatial-temporal tree
Taxi is one of the important means of transportation for people's daily travel activities, and it
is one of the important research objects of intelligent transportation system. Taxi demand …
is one of the important research objects of intelligent transportation system. Taxi demand …
A multi-directional recurrent graph convolutional network model for reconstructing traffic spatiotemporal diagram
ABSTRACT The Time Space Diagram (TSD) can abstractly represent multiple data sources
and the macroscopic state of road traffic. However, the TSDs may be incomplete due to …
and the macroscopic state of road traffic. However, the TSDs may be incomplete due to …
I Open at the Close: A Deep Reinforcement Learning Evaluation of Open Streets Initiatives
RT Witter, L Rosenblatt - Proceedings of the AAAI Conference on …, 2024 - ojs.aaai.org
The open streets initiative" opens" streets to pedestrians and bicyclists by closing them to
cars and trucks. The initiative, adopted by many cities across North America, increases …
cars and trucks. The initiative, adopted by many cities across North America, increases …
Physical Attention-Gated Spatial-Temporal Predictive Network for Weather Forecasting
X Zhao, Q Sun, X Lin - Mathematics, 2023 - mdpi.com
Spatial-temporal sequence prediction is one of the hottest topics in the field of deep learning
due to its wide range of potential applications in video-like data processing, specifically …
due to its wide range of potential applications in video-like data processing, specifically …
The Real-Time Dynamic Prediction of Optimal Taxi Cruising Area Based on Deep Learning
S Wang, J Wang, C Ma, D Li, L Cai - Sustainability, 2024 - mdpi.com
A real-time, effective, and dynamic taxi cruising recommendation strategy is essential to
solving the problem of taxi cruising passenger difficulty and urban road traffic congestion …
solving the problem of taxi cruising passenger difficulty and urban road traffic congestion …
[PDF][PDF] Spatio-temporal information enhance graph convolutional networks: A deep learning framework for ride-hailing demand prediction
Z Tang, C Chen - Mathematical Biosciences and Engineering, 2024 - aimspress.com
Ride-hailing demand prediction is essential in fundamental research areas such as
optimizing vehicle scheduling, improving service quality, and reducing urban traffic …
optimizing vehicle scheduling, improving service quality, and reducing urban traffic …
Implementation of AI in Traffic Management: Need, current techniques and challenges
In the most recent years, technology, including Artificial Intelligence (AI) has advanced in
every industry conceivable. Artificial Intelligence has been a keen area of interest in solving …
every industry conceivable. Artificial Intelligence has been a keen area of interest in solving …
Diseño y mejora de un predictor de tráfico basado en GNN
M Fauvell Monfort - 2023 - e-spacio.uned.es
En este trabajo se realiza un estudio sobre el efecto de las formas de construcción de grafos
y los efectos de las diferentes características disponibles. La previsión de tráfico es un …
y los efectos de las diferentes características disponibles. La previsión de tráfico es un …
[PDF][PDF] 대리운전시장의지역별수요예측모형의성능향상을위한방법론연구
김민섭， 박기군， 허재현， 권재은， 배혜림 - 한국빅데이터논문지제, 2023 - researchgate.net
요 약대리운전 시장의 요금체계는 이용자의 대리운전 서비스 요청 시, 주위 대리운전 기사의 수,
대리운전 서비스이용자 수, 날씨 등의 다양한 영향에 의해 실시간으로 변하는 Dynamic Pricing …
대리운전 서비스이용자 수, 날씨 등의 다양한 영향에 의해 실시간으로 변하는 Dynamic Pricing …