A math-heuristic approach for scheduling the production and delivery of a mobile additive manufacturing hub DOI
Yali Gao, Biao Yuan, Weiwei Cui

et al.

Computers & Industrial Engineering, Journal Year: 2024, Volume and Issue: 188, P. 109929 - 109929

Published: Jan. 25, 2024

Language: Английский

Applications of machine learning in friction stir welding: Prediction of joint properties, real-time control and tool failure diagnosis DOI
Ammar H. Elsheikh

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 121, P. 105961 - 105961

Published: Feb. 14, 2023

Language: Английский

Citations

145

An adaptive differential evolution algorithm based on belief space and generalized opposition-based learning for resource allocation DOI
Wu Deng, Hongcheng Ni,

Yi Liu

et al.

Applied Soft Computing, Journal Year: 2022, Volume and Issue: 127, P. 109419 - 109419

Published: Aug. 2, 2022

Language: Английский

Citations

133

Multi-strategy particle swarm and ant colony hybrid optimization for airport taxiway planning problem DOI
Wu Deng, Lirong Zhang, Xiangbing Zhou

et al.

Information Sciences, Journal Year: 2022, Volume and Issue: 612, P. 576 - 593

Published: Sept. 6, 2022

Language: Английский

Citations

123

Co-evolutionary competitive swarm optimizer with three-phase for large-scale complex optimization problem DOI
Chen Huang, Xiangbing Zhou,

Xiaojuan Ran

et al.

Information Sciences, Journal Year: 2022, Volume and Issue: 619, P. 2 - 18

Published: Nov. 11, 2022

Language: Английский

Citations

119

Adaptive cylinder vector particle swarm optimization with differential evolution for UAV path planning DOI
Chen Huang, Xiangbing Zhou,

Xiaojuan Ran

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 121, P. 105942 - 105942

Published: Feb. 9, 2023

Language: Английский

Citations

104

Multi-strategy competitive-cooperative co-evolutionary algorithm and its application DOI
Xiangbing Zhou,

Xing Cai,

Hua Zhang

et al.

Information Sciences, Journal Year: 2023, Volume and Issue: 635, P. 328 - 344

Published: March 30, 2023

Language: Английский

Citations

83

An enhanced distributed differential evolution algorithm for portfolio optimization problems DOI
Yingjie Song, Gaoyang Zhao, Bin Zhang

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 121, P. 106004 - 106004

Published: Feb. 25, 2023

Language: Английский

Citations

74

Transfer learning based on improved stacked autoencoder for bearing fault diagnosis DOI
Shuyang Luo, Xufeng Huang, Yanzhi Wang

et al.

Knowledge-Based Systems, Journal Year: 2022, Volume and Issue: 256, P. 109846 - 109846

Published: Sept. 3, 2022

Language: Английский

Citations

73

ABC-GSPBFT: PBFT with grouping score mechanism and optimized consensus process for flight operation data-sharing DOI
Junjie Xu,

Yali Zhao,

Huayue Chen

et al.

Information Sciences, Journal Year: 2022, Volume and Issue: 624, P. 110 - 127

Published: Dec. 27, 2022

Language: Английский

Citations

67

Vibration and infrared thermography based multiple fault diagnosis of bearing using deep learning DOI
Tauheed Mian, Anurag Choudhary, Shahab Fatima

et al.

Nondestructive Testing And Evaluation, Journal Year: 2022, Volume and Issue: 38(2), P. 275 - 296

Published: Sept. 5, 2022

The occurrence of multiple faults is a practical problem in the bearings rotating machines, and early diagnosis such issues an intelligent manner vital era industry 4.0. present work investigated various combinations bearing faults, including dual fault conditions. Two prevalent methods were employed: vibration monitoring using time-frequency scalograms extracted through Continuous Wavelet Transform (CWT) non-invasive Infrared Thermography (IRT). A 2-D Convolutional Neural Network (CNN) was used to classify conditions automated feature extraction. proposed methodology validated at two constant speed 19 Hz 29 continuously accelerated decelerated range - Hz. Adequate accuracy achieved both case vibration-based diagnosis, with 99.39 % 99.97 %. Meanwhile, IRT-based 100 classification for all These results signify robustness reliability varying

Language: Английский

Citations

65