A novel machine learning model for safety risk analysis in flywheel-battery hybrid energy storage system

Z Wen, P Fang, Y Yin, G Krolczyk, P Gardoni… - Journal of Energy …, 2022 - Elsevier
Flywheel energy storage system (FESS) has been regarded as the most promising hybrid
storage technique to manage the battery charging process of electric vehicles. Thanks to …

[HTML][HTML] A hybrid deep learning method for the prediction of ship time headway using automatic identification system data

Q Ma, X Du, C Liu, Y Jiang, Z Liu, Z Xiao… - … Applications of Artificial …, 2024 - Elsevier
Abstract Ship Time Headway (STH) is used in maritime navigation to describe the time
interval between the arrivals of two consecutive ships in the same water area. This …

Understanding urban bus travel time: Statistical analysis and a deep learning prediction

Y Liu, H Zhang, J Jia, B Shi, W Wang - International Journal of …, 2023 - World Scientific
Travel time reliability plays a key role in bus scheduling and service quality. Owing to
various stochastic factors, buses often suffer from traffic congestion, delay and bunching …

A novel hybrid STL-transformer-ARIMA architecture for aviation failure events prediction

H Zeng, H Zhang, J Guo, B Ren, L Cui, J Wu - Reliability Engineering & …, 2024 - Elsevier
Accurate prediction of aviation failure events helps to anticipate future safety situations and
protect against further uncontrollable accidents. However, the large sample size, complex …

An Effective Method for Underwater Biological Multi-Target Detection Using Mask Region-Based Convolutional Neural Network

Z Yue, B Yan, H Liu, Z Chen - Water, 2023 - mdpi.com
Underwater creatures play a vital role in maintaining the delicate balance of the ocean
ecosystem. In recent years, machine learning methods have been developed to identify …

Short-term prediction of the significant wave height and average wave period based on the variational mode decomposition–temporal convolutional network–long …

Q Ji, L Han, L Jiang, Y Zhang, M Xie, Y Liu - Ocean Science, 2023 - os.copernicus.org
The present work proposes a prediction model of significant wave height (SWH) and
average wave period (APD) based on variational mode decomposition (VMD), temporal …

Fusion deep learning and machine learning for heterogeneous military entity recognition

H Li, L Yu, J Zhang, M Lyu - Wireless Communications and …, 2022 - Wiley Online Library
With respect to the fuzzy boundaries of military heterogeneous entities, this paper improves
the entity annotation mechanism for entity with fuzzy boundaries based on related research …

Double graph attention actor-critic framework for urban bus-pooling system

E Wang, B Liu, S Lin, F Shen, T Bao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
To unleash the power of buses, we propose a bus-pooling system that keeps the notion of
bus stops and terminals but discards the concept of fixed bus lines by enabling buses to …

Limited information limits accuracy: Whether ensemble empirical mode decomposition improves crude oil spot price prediction?

K Xu, W Wang - International Review of Financial Analysis, 2023 - Elsevier
A reliable crude oil price forecast is important for market pricing. Despite the widespread use
of ensemble empirical mode decomposition (EEMD) in financial time series forecasting, the …

Exploring the determinants of public transport usage and shared mobilities: A case study from Nanchang, China

T Zhou, J Zhang, L Peng, S Zhang - Sustainable Cities and Society, 2022 - Elsevier
Shared mobility became popularized in many urban cities as new sustainable transport
pattern that provides multimodal and flexible mobility solutions. In order to derive a …