Deep learning for spatio-temporal data mining: A survey

S Wang, J Cao, SY Philip - IEEE transactions on knowledge …, 2020 - ieeexplore.ieee.org
With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

Deep learning applications in manufacturing operations: a review of trends and ways forward

S Sahoo, S Kumar, MZ Abedin, WM Lim… - Journal of Enterprise …, 2023 - emerald.com
Purpose Deep learning (DL) technologies assist manufacturers to manage their business
operations. This research aims to present state-of-the-art insights on the trends and ways …

A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data

X Ma, Y Ji, Y Yuan, N Van Oort, Y **… - … Research Part A: Policy …, 2020 - Elsevier
The co-existence of traditional docked bike-sharing and emerging dockless systems
presents new opportunities for sustainable transportation in cities all over the world, both …

Predicting station-level hourly demand in a large-scale bike-sharing network: A graph convolutional neural network approach

L Lin, Z He, S Peeta - Transportation Research Part C: Emerging …, 2018 - Elsevier
This study proposes a novel Graph Convolutional Neural Network with Data-driven Graph
Filter (GCNN-DDGF) model that can learn hidden heterogeneous pairwise correlations …

Data analytics in the supply chain management: Review of machine learning applications in demand forecasting

A Aamer, LP Eka Yani… - Operations and Supply …, 2020 - journal.oscm-forum.org
In today's fast-paced global economy coupled with the availability of mobile internet and
social networks, several business models have been disrupted. This disruption brings a …

A temporal fusion transformer for short-term freeway traffic speed multistep prediction

H Zhang, Y Zou, X Yang, H Yang - Neurocomputing, 2022 - Elsevier
Accurate short-term freeway speed prediction is a key component for intelligent
transportation management and can help travelers plan travel routes. However, very few …

Sequence to sequence learning with attention mechanism for short-term passenger flow prediction in large-scale metro system

S Hao, DH Lee, D Zhao - Transportation Research Part C: Emerging …, 2019 - Elsevier
The accurate short-term passenger flow prediction is of great significance for real-time public
transit management, timely emergency response as well as systematical medium and long …

Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

MM Bassiouni, RK Chakrabortty, OK Hussain… - Expert Systems with …, 2023 - Elsevier
The ongoing COVID-19 pandemic has created an unprecedented predicament for global
supply chains (SCs). Shipments of essential and life-saving products, ranging from …

Machine learning for geographically differentiated climate change mitigation in urban areas

N Milojevic-Dupont, F Creutzig - Sustainable Cities and Society, 2021 - Elsevier
Artificial intelligence and machine learning are transforming scientific disciplines, but their
full potential for climate change mitigation remains elusive. Here, we conduct a systematic …

A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system

Y Du, F Deng, F Liao - Transportation Research Part C: Emerging …, 2019 - Elsevier
Public bike-sharing has gained much attention with the tide of sharing economy.
Empowered by modern technologies (eg, GPS devices and smartphone-based APPs), a …