output
20162019
most citedWasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis

271 citations

9 papers

cs.LG2019★ 271 cited

Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis

Cheng Cheng, Beitong Zhou, Guijun Ma +2

The demand of artificial intelligent adoption for condition-based maintenance strategy is astonishingly increased over the past few years. Intelligent fault diagnosis is one critic…

cs.LG2019★ 165 cited

A General End-to-end Diagnosis Framework for Manufacturing Systems

Ye Yuan, Guijun Ma, Cheng Cheng +4

The manufacturing sector is envisioned to be heavily influenced by artificial intelligence-based technologies with the extraordinary increases in computational power and data volum…

cs.NE2018

Differential Evolution with Better and Nearest Option for Function Optimization

Haozhen Dong, Liang Gao, Xinyu Li +2

Differential evolution(DE) is a conventional algorithm with fast convergence speed. However, DE may be trapped in local optimal solution easily. Many researchers devote themselves…

cs.LG2018★ 235 cited

A deep learning-based remaining useful life prediction approach for bearings

Cheng Cheng, Guijun Ma, Yong Zhang +4

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining usef…

eess.SY2018★ 197 cited

Data-driven Discovery of Cyber-Physical Systems

Ye Yuan, Xiuchuan Tang, Wei Pan +5

Cyber-physical systems (CPSs) embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, intelligent manufacture and medical…

cs.CE2018★ 41 cited

Topology optimization of micro-structured materials featured with the specific mechanical properties

Jie Gao, Hao Li, Zhen Luo +2

Micro-structured materials consisting of an array of microstructures are engineered to provide the specific material properties. This present work investigates the design of cellul…

physics.soc-ph2018★ 109 cited

Link prediction via linear optimization

Ratha Pech, Dong Hao, Yan-Li Lee +2

Link prediction is an elemental challenge in network science, which has already found applications in guiding laboratorial experiments, digging out drug targets, recommending frien…

cs.NE2018★ 26 cited

Whale swarm algorithm with the mechanism of identifying and escaping from extreme points for multimodal function optimization

Bing Zeng, Xinyu Li, Liang Gao +2

Most real-world optimization problems often come with multiple global optima or local optima. Therefore, increasing niching metaheuristic algorithms, which devote to finding multip…

eess.SY2016★ 27 cited

On the Powerball Method for Optimization

Ye Yuan, Mu Li, Jun Liu +1

We propose a new method to accelerate the convergence of optimization algorithms. This method simply adds a power coefficient to the gradient during optimization. We ca…