This talk discusses a nonlinear regression simulation applied to dynamic modelling. Since the actual mathematical model of raw data collected from an experiment or a process is unknown, we can only observe the pattern and trend presented by the raw data. Thus, modelling these raw data will give us valuable information to understand the process. We propose a simplified model and introduce a least square optimization model for this modelling, aiming to measure the differences between the model and the raw data. Through deriving the first-order necessary conditions, the model parameters are determined iteratively, in turn, to minimize the differences between the model and the raw data. Therefore, we simulate a nonlinear regression with a simplified model to deal with raw data. For illustration, we studied some examples and presented their results. The simplified model shows the accuracy of the results satisfactorily since the mean square error value is small. For future research, we recommend applying the simplified model to approximate the solution of more complex nonlinear dynamical systems.   

Keywords: Nonlinear Regression, Dynamic Modelling, Least Square Optimization, Simplified Model, Mean Square Error 

Sie Long Kek, PhD, CQRM, is currently a senior lecturer in the Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia (Pagoh Campus). He received his M.Sc. and Ph.D. in mathematics from Universiti Teknologi Malaysia, Johor, Malaysia, in 2002 and 2011, respectively. He was a research associate at the Curtin University of Technology in 2009 during his Ph.D. study. His research interests include optimization and control, operational research and management science, modelling and simulation, parameter estimation, Kalman filtering, and computational mathematics. He has published over 50 papers in refereed journals and six (6) book chapters. He reviews peer-reviewed research journals, including Automatica, Optimal Control, Applications and Methods, International Journal of Control, Heliyon, Journal of Industrial and Management Optimization, Measurement and Control, Hindawi Journal of Mathematics and MDPI Journal of Risk and Financial Management. He has hosted two (3) research projects supported by the Ministry of Education Malaysia. He has supervised five (5) master's and three (3) Ph.D. students. Since 2015, he is a certified quantitative risk management (CQRM) fellow. From 2021 to 2023, he was appointed head of the research focus group, Numerical Simulation and Applications (NSA).   

Email: slkek@uthm.edu.my 

UTHM Staf Profile: https://community.uthm.edu.my/slkek 

SCOPUS ID: 35776335100

ORCID ID: 0000-0003-0425-4422

Publons ID: H-6498-2011

Google Scholar: https://scholar.google.com.my/citations?user=wWntPq4AAAAJ&hl=en