Versita

Józef Korbicz

jozef-korbicz

Professor, Corresponding member of the Polish Academy of Sciences
Institute of Control and Computation Engineering
University of Zielona Góra, Poland
E-mail: J.Korbicz@issi.uz.zgora.pl
Page: http://www.uz.zgora.pl/~jkorbicz/

Fields of interest:

  • Soft computing: methods and techniques: artifical neural networks (optimization of multilayer networks, GMDH (Group Methods of Data Handling) networks and their extensions, networks with the dynamic model of neurons), fuzzy and neuro-fuzzy systems (structure and parameter optimization), bounded-error analysis, expert systems
  • Fault diagnosis: analytical methods (model-based approach, robust observers, unknown input observers); soft computing techniques (neural and neuro-fuzzy models, classifiers, optimization of diagnostic systems, expert systems)
  • Modelling and simulation: distributed parameter systems (modelling, state and parameter estimation, sensors and actuators location), application (sugar and power plants, air pollution processes)

 

Recent publications:

M. Mrugalski, M. Witczak, J. Korbicz:
Confidence estimation of the multi-layer perceptron and its application in fault detection systems,
Engineering Applications of Artificial Intelligence, Vol. 21(8),
(2008),  pp. 895-906.

J. Korbicz, M. Mrugalski:
Confidence estimation of GMDH neural networks and its application in fault detection systems,
International Journal of Systems Science, Vol. 39(8), (2008), pp. 783-800.

J. Korbicz:
Fault diagnosis of non-linear dynamical systems using analytical and soft computing methods,
Journal of Automation, Mobile Robotics & Intelligent Systems, Vol. 1,
(2007), pp. 7-23.

M. Witczak, J. Korbicz, M Mrugalski, R.J. Patton:
A GMDH neural network-based approach to robust fault diagnosis: Application to the DAMADICS benchmark problem,
Control Engineering Practice, CEP, Vol. 14(6), (2006), pp. 671-683.

J. Korbicz, M. Kowal: 
Neuro-fuzzy networks and their application to fault detection of dynamical systems,
Engng. Appl. of Artificial Intelligence, Vol. 20, (2007), pp. 609-617.

J. Korbicz: 
Robust fault detection using analytical and soft computing methods,
Bulletin of the Polish Academy Sciences: Technical Sciences, Vol. 54(1),
(2006),  pp. 75-88.

J. Korbicz, J.M. Kościelny, Z. Kowalczuk, W. Cholewa:
Fault Diagnosis. Models, Artificial Intelligence, Applications,
Berlin Heidelberg: Springer-Verlag, 2004, 920p.