Comparative review of the blockchain consensus algorithm between proof of stake (pos) and delegated proof of stake (dpos)

SMS Saad, RZRM Radzi - International Journal of Innovative Computing, 2020 - ijic.utm.my
Blockchain is a public ledger technology to which everyone has access without a central
authority having control. This technology typically gets to use registration and smart contract …

A hybrid CEEMD-GMM scheme for enhancing the detection of traffic flow on highways

H Dou, Y Liu, S Chen, H Zhao, H Bilal - Soft Computing, 2023 - Springer
Many highways are acquiring smart transportation systems to improve traffic efficiency,
safety and management. Intelligent transportation systems can monitor traffic congestion by …

Modeling of dynamical systems through deep learning

P Rajendra, V Brahmajirao - Biophysical Reviews, 2020 - Springer
This review presents a modern perspective on dynamical systems in the context of current
goals and open challenges. In particular, our review focuses on the key challenges of …

Fine-grained vessel traffic flow prediction with a spatio-temporal multigraph convolutional network

M Liang, RW Liu, Y Zhan, H Li, F Zhu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The accurate and robust prediction of vessel traffic flow is gaining importance in maritime
intelligent transportation system (ITS), such as vessel traffic services, maritime spatial …

Multitask hypergraph convolutional networks: A heterogeneous traffic prediction framework

J Wang, Y Zhang, L Wang, Y Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Traffic prediction methods on a single-source data have achieved excellent results in recent
years, especially the Graph Convolutional Networks (GCN) based models with spatio …

SeaBil: Self-attention-weighted ultrashort-term deep learning prediction of ship maneuvering motion

N Wang, X Kong, B Ren, L Hao, B Han - Ocean Engineering, 2023 - Elsevier
Accurate prediction of motion dynamics fundamentally promotes the autonomy of intelligent
ships, but faces great challenges in modeling mechanism. In this paper, to establish data …

A combined deep learning method with attention‐based LSTM model for short‐term traffic speed forecasting

P Wu, Z Huang, Y Pian, L Xu, J Li… - Journal of Advanced …, 2020 - Wiley Online Library
Short‐term traffic speed prediction is a promising research topic in intelligent transportation
systems (ITSs), which also plays an important role in the real‐time decision‐making of traffic …

Short-term traffic flow prediction based on secondary hybrid decomposition and deep echo state networks

G Hu, RW Whalin, TA Kwembe, W Lu - Physica A: Statistical Mechanics and …, 2023 - Elsevier
Short-term traffic flow prediction is a significant and challenging research topic as it is closely
related to the application of intelligent transportation systems. Due to the variable and …

On the use of dynamic mode decomposition for time-series forecasting of ships operating in waves

A Serani, P Dragone, F Stern, M Diez - Ocean engineering, 2023 - Elsevier
In order to guarantee the safety of payload, crew, and structures, ships must exhibit good
seakee**, maneuverability, and structural-response performance, also when they operate …

[HTML][HTML] Koopman theory meets graph convolutional network: Learning the complex dynamics of non-stationary highway traffic flow for spatiotemporal prediction

T Wang, D Ngoduy, Y Li, H Lyu, G Zou… - Chaos, Solitons & …, 2024 - Elsevier
Reliable and accurate traffic flow prediction is crucial for the construction and operation of
smart highways, supporting scientific traffic management and planning. However, accurately …