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Khodabandehlou, Hamid
15  results:
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1

Cell culture product quality attribute prediction using con..:

Khodabandehlou, Hamid ; Rashedi, Mohammad ; Wang, Tony...
Biotechnology and Bioengineering.  121 (2024)  4 - p. 1230-1242 , 2024
Link: https://doi.org/10.1002/..
 
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2

Integration of just‐in‐time learning with variational autoe..:

Rashedi, Mohammad ; Khodabandehlou, Hamid ; Wang, Tony...
Biotechnology and Bioengineering.  121 (2024)  7 - p. 2205-2224 , 2024
Link: https://doi.org/10.1002/..
 
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3

Machine learning‐based model predictive controller design f..:

Rashedi, Mohammad ; Rafiei, Mina ; Demers, Matthew...
Biotechnology and Bioengineering.  120 (2023)  8 - p. 2144-2159 , 2023
Link: https://doi.org/10.1002/..
 
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4

Spectroscopic models for real‐time monitoring of cell cultu..:

Tulsyan, Aditya ; Khodabandehlou, Hamid ; Wang, Tony...
AIChE Journal.  67 (2021)  5 - p. , 2021
Link: https://doi.org/10.1002/..
 
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5

Networked model predictive control using a wavelet neural n..:

Khodabandehlou, Hamid ; Fadali, Mohammed Sami
Advanced Control for Applications.  2 (2020)  4 - p. , 2020
Link: https://doi.org/10.1002/..
 
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6

Automatic real‐time calibration, assessment, and maintenanc..:

Tulsyan, Aditya ; Wang, Tony ; Schorner, Gregg...
Biotechnology and Bioengineering.  117 (2019)  2 - p. 406-416 , 2019
Link: https://doi.org/10.1002/..
 
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7

A machine‐learning approach to calibrate generic Raman mode..:

Tulsyan, Aditya ; Schorner, Gregg ; Khodabandehlou, Hamid...
Biotechnology and Bioengineering.  116 (2019)  10 - p. 2575-2586 , 2019
Link: https://doi.org/10.1002/..
 
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8

Training recurrent neural networks via dynamical trajectory..:

Khodabandehlou, Hamid ; Sami Fadali, M.
Neurocomputing.  368 (2019)  - p. 1-10 , 2019
Link: https://doi.org/10.1016/..
 
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9

Event Classification in Distribution Networks Using a Quoti..:

, In: 2019 North American Power Symposium (NAPS),
Khodabandehlou, Hamid ; Niazazari, Iman ; Livani, Hanif. - p. 1-6 , 2019
Link: https://doi.org/10.1109/..
 
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10

Adaptive Matching Pursuit based Online Identification and C..:

Khodabandehlou, Hamid
http://arxiv.org/abs/1803.01897.  , 2018
Link: http://arxiv.org/abs/180..
 
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11

Training Recurrent Neural Networks as a Constraint Satisfac..:

Khodabandehlou, Hamid ; Fadali, M. Sami
http://arxiv.org/abs/1803.07200.  , 2018
Link: http://arxiv.org/abs/180..
 
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12

Nonlinear System Identification using Neural Networks and T..:

Khodabandehlou, Hamid ; Fadali, Mohammed Sami
http://arxiv.org/abs/1804.10346.  , 2018
Link: http://arxiv.org/abs/180..
 
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13

Anomaly Classification in Distribution Networks Using a Quo..:

Khodabandehlou, Hamid ; Niazazari, Iman ; Livani, Hanif.
http://arxiv.org/abs/1805.04979.  , 2018
Link: http://arxiv.org/abs/180..
 
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14

Training Recurrent Neural Networks via Dynamical Trajectory..:

Khodabandehlou, Hamid ; Fadali, M. Sami
http://arxiv.org/abs/1805.04152.  , 2018
Link: http://arxiv.org/abs/180..
 
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15

Anticipating of ash agglomeration behavior in a fluidized b..:

Khodabandehlou, Ramin ; Kirschenmann, Dominik ; Schimpke, Ronny...
Fuel.  358 (2024)  - p. 130252 , 2024
Link: https://doi.org/10.1016/..
 
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