activity
20192021
most citedRemaining Useful Life Estimation Using Functional Data Analysis

19 citations · 49 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2021★ 2 cited

Deep Time Series Models for Scarce Data

Qiyao Wang, Ahmed Farahat, Chetan Gupta +1

Time series data have grown at an explosive rate in numerous domains and have stimulated a surge of time series modeling research. A comprehensive comparison of different time seri…

cs.LG2020★ 3 cited

Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning

Chi Zhang, Philip Odonkor, Shuai Zheng +3

Dynamic dispatching is one of the core problems for operation optimization in traditional industries such as mining, as it is about how to smartly allocate the right resources to t…

cs.LG2019★ 13 cited

Manufacturing Dispatching using Reinforcement and Transfer Learning

Shuai Zheng, Chetan Gupta, Susumu Serita

Efficient dispatching rule in manufacturing industry is key to ensure product on-time delivery and minimum past-due and inventory cost. Manufacturing, especially in the developed w…

cs.LG2019★ 12 cited

Generative Adversarial Networks for Failure Prediction

Shuai Zheng, Ahmed Farahat, Chetan Gupta

Prognostics and Health Management (PHM) is an emerging engineering discipline which is concerned with the analysis and prediction of equipment health and performance. One of the ke…

cs.LG2019★ 19 cited

Remaining Useful Life Estimation Using Functional Data Analysis

Qiyao Wang, Shuai Zheng, Ahmed Farahat +2

Remaining Useful Life (RUL) of an equipment or one of its components is defined as the time left until the equipment or component reaches its end of useful life. Accurate RUL estim…