| 1 |
Recursive NARX model identification of nonlinear chemical processes with matrix invertibility analysis
Dong JF
Computers & Chemical Engineering, 121, 574, 2019 |
| 2 |
The effects of linear and nonlinear characteristic parameters on the output frequency responses of nonlinear systems: The associated output frequency response function
Zhu YP, Lang ZQ
Automatica, 93, 422, 2018 |
| 3 |
Sparse Bayesian Nonlinear System Identification Using Variational Inference
Jacobs WR, Baldacchino T, Dodd T, Anderson SR
IEEE Transactions on Automatic Control, 63(12), 4172, 2018 |
| 4 |
An artificial neural network to assess the impact of neighbouring photovoltaic systems in power forecasting in Utrecht, the Netherlands
Vaz AGR, Elsinga B, van Sark WGJHM, Brito MC
Renewable Energy, 85, 631, 2016 |
| 5 |
Nonlinear Autoregressive Exogenous modeling of a large anaerobic digester producing biogas from cattle waste
Dhussa AK, Sambi SS, Kumar S, Kumar S, Kumar S
Bioresource Technology, 170, 342, 2014 |
| 6 |
Predicting oil price movements: A dynamic Artificial Neural Network approach
Godarzi AA, Amiri RM, Talaei A, Jamasb T
Energy Policy, 68, 371, 2014 |
| 7 |
Magnitude bounds of generalized frequency response functions for nonlinear Volterra systems described by NARX model
Jing XJ, Lang ZQ, Billings SA
Automatica, 44(3), 838, 2008 |
| 8 |
Modelling and identification of non-linear deterministic systems in the delta-domain
Anderson SR, Kadirkamanathan V
Automatica, 43(11), 1859, 2007 |
| 9 |
Approximate dynamic programming-based approaches for input-output data-driven control of nonlinear processes
Lee JM, Lee JH
Automatica, 41(7), 1281, 2005 |
