Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Hamid Khodabandehlou"'
Publikováno v:
IFAC-PapersOnLine. 55:45-50
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a3bdc148943024ebe25125e47458ce1
https://doi.org/10.1016/j.ifacol.2022.07.420
https://doi.org/10.1016/j.ifacol.2022.07.420
Autor:
M. Sami Fadali, Hamid Khodabandehlou
Publikováno v:
Neurocomputing. 368:1-10
This paper introduces a new method to train recurrent neural networks using dynamical trajectory-based optimization. The optimization method utilizes a projected gradient system (PGS) and a quotient gradient system (QGS) to determine the feasible reg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3109fab4009db228e427a28cb15f96bc
https://doi.org/10.1016/j.neucom.2019.08.058
https://doi.org/10.1016/j.neucom.2019.08.058
Publikováno v:
Biotechnology and Bioengineering. 116:2575-2586
The manufacture of biotherapeutic proteins consists of complex upstream unit operations requiring multiple raw materials, analytical techniques, and control strategies to produce safe and consistent products for patients. Raman spectroscopy is a ubiq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::135cfa8636d416000c9c3211d5419eed
https://doi.org/10.1002/bit.27100
https://doi.org/10.1002/bit.27100
Publikováno v:
AIChE Journal. 67
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f0f2c23ecc1dbcc291480ee750abc7f
https://doi.org/10.1002/aic.17210
https://doi.org/10.1002/aic.17210
Autor:
Hamid Khodabandehlou, M. Sami Fadali
Publikováno v:
Advanced Control for Applications. 2
In this study, we use a wavelet neural network with a feedforward component and a model predictive controller for online nonlinear system identification over a communication network. The wavelet neural network (WNN) performs the online identification
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef3fa57c80be9ef471181b8f8ea72a02
https://doi.org/10.1002/adc2.55
https://doi.org/10.1002/adc2.55
Publikováno v:
IFAC-PapersOnLine. 50:2800-2805
This paper examines two popular neural networks that have been successfully utilized in a wide variety of applications: echo state networks (ESN) and wavelet neural networks (WNN). It introduces innovations in the structure of ESN that result in majo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe09a722d52fb065193974aed87eb994
https://doi.org/10.1016/j.ifacol.2017.08.630
https://doi.org/10.1016/j.ifacol.2017.08.630
Publikováno v:
2019 North American Power Symposium (NAPS).
The classification of events or sudden changes in power networks versus normal abrupt changes or switching actions is essential to take appropriate maintenance actions that guarantee the quality of power delivery. This issue has increased in importan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffbf072e68aab4687dc22564b347d765
https://doi.org/10.1109/naps46351.2019.8999976
https://doi.org/10.1109/naps46351.2019.8999976
Publikováno v:
Biotechnology and bioengineeringREFERENCES. 117(2)
Raman spectroscopy is a multipurpose analytical technology that has found great utility in real-time monitoring and control of critical performance parameters of cell culture processes. As a process analytical technology (PAT) tool, the performance o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c68ffabe53a6094ff651ae6c513311a
https://pubmed.ncbi.nlm.nih.gov/31631322
https://pubmed.ncbi.nlm.nih.gov/31631322
Publikováno v:
ICINCO (1)
In this paper, we study the identification of two challenging benchmark problems using neural networks. Two different global optimization approaches are used to train a recurrent neural network to identify two challenging nonlinear models, the cascad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e6d784c0034c18f5b8ef579ca7ada8a
http://arxiv.org/abs/1804.10346
http://arxiv.org/abs/1804.10346
Publikováno v:
IJCNN
In this study we introduce a new approach to train a fully recurrent artificial neural network by solving a constraint satisfaction problem using the quotient gradient method. The quotient gradient method is a trajectory based methodology for global
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5edc3330203b4bf9f431aac7a99763e
https://doi.org/10.1109/ijcnn.2017.7966170
https://doi.org/10.1109/ijcnn.2017.7966170