Spremljaj
Abdallah A Chehade
Abdallah A Chehade
Associate Professor at the University of Michigan-Dearborn
Preverjeni e-poštni naslov na umich.edu - Domača stran
Naslov
Navedeno
Navedeno
Leto
A dual-LSTM framework combining change point detection and remaining useful life prediction
Z Shi, A Chehade
Reliability Engineering & System Safety 205, 107257, 2021
2982021
Optimize the signal quality of the composite health index via data fusion for degradation modeling and prognostic analysis
K Liu, A Chehade, C Song
IEEE Transactions on Automation Science and Engineering 14 (3), 1504-1514, 2015
1542015
A controllable deep transfer learning network with multiple domain adaptation for battery state-of-charge estimation
I Oyewole, A Chehade, Y Kim
Applied Energy 312, 118726, 2022
932022
A data-level fusion approach for degradation modeling and prognostic analysis under multiple failure modes
A Chehade, C Song, K Liu, A Saxena, X Zhang
Journal of Quality Technology 50 (2), 150-165, 2018
882018
Sensory-Based Failure Threshold Estimation for Remaining Useful Life Prediction
A Chehade, S Bonk, K Liu
IEEE Transactions on Reliability, 1-11, 2017
732017
A collaborative Gaussian process regression model for transfer learning of capacity trends between li-ion battery cells
AA Chehade, AA Hussein
IEEE Transactions on Vehicular Technology 69 (9), 9542-9552, 2020
542020
Robust artificial neural network-based models for accurate surface temperature estimation of batteries
AA Hussein, AA Chehade
IEEE Transactions on Industry Applications 56 (5), 5269-5278, 2020
522020
Sensor fusion via statistical hypothesis testing for prognosis and degradation analysis
A Chehade, Z Shi
IEEE Transactions on Automation Science and Engineering 16 (4), 1774-1787, 2019
522019
Control Theoretical Modeling of Transient Behavior of Production Planning and Control: A Review
N Duffie, A Chehade, A Athavale
Proc. of 44th CIRP Conf. on Mfg. Sys., Windsor, ON, 2014
382014
A multioutput convolved Gaussian process for capacity forecasting of li-ion battery cells
AA Chehade, AA Hussein
IEEE Transactions on Power Electronics 37 (1), 896-909, 2021
362021
Uncorrelated sparse autoencoder with long short-term memory for state-of-charge estimations in lithium-ion battery cells
M Savargaonkar, I Oyewole, A Chehade, AA Hussein
IEEE Transactions on Automation Science and Engineering 21 (1), 15-26, 2022
292022
Conditional Gaussian mixture model for warranty claims forecasting
A Chehade, M Savargaonkar, V Krivtsov
Reliability Engineering & System Safety 218, 108180, 2022
262022
Dynamics of autonomously acting products and work systems in production and assembly
O Jeken, N Duffie, K Windt, H Blunck, A Chehade, H Rekersbrink
CIRP Journal of Manufacturing Science and Technology 5 (4), 267-275, 2012
262012
An adaptive deep neural network with transfer learning for state-of-charge estimations of battery cells
M Savargaonkar, A Chehade
2020 IEEE Transportation Electrification Conference & Expo (ITEC), 598-602, 2020
202020
Structural degradation modeling framework for sparse data sets with an application on Alzheimer’s disease
A Chehade, K Liu
IEEE Transactions on Automation Science and Engineering 16 (1), 192-205, 2018
202018
A novel neural network with Gaussian process feedback for modeling the state-of-charge of battery cells
M Savargaonkar, A Chehade, AA Hussein
IEEE Transactions on Industry Applications 58 (4), 5340-5352, 2022
192022
The effect of vehicle automation styles on drivers’ emotional state
A Alsaid, JD Lee, SI Noejovich, A Chehade
IEEE Transactions on Intelligent Transportation Systems 24 (4), 3963-3973, 2023
162023
A multi-output convolved Gaussian process model for capacity estimation of electric vehicle Li-ion battery cells
AA Chehade, AA Hussein
2019 IEEE Transportation Electrification Conference and Expo (ITEC), 1-4, 2019
152019
A long short-term memory network for online state-of-charge estimation of li-ion battery cells
Z Shi, M Savargaonkar, AA Chehade, AA Hussein
2020 IEEE Transportation Electrification Conference & Expo (ITEC), 594-597, 2020
132020
A cycle-based recurrent neural network for state-of-charge estimation of li-ion battery cells
M Savargaonkar, A Chehade, Z Shi, AA Hussein
2020 IEEE Transportation Electrification Conference & Expo (ITEC), 584-587, 2020
122020
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