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Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with a moving measurement window

Kazimierz Duzinkiewicz — 2006

International Journal of Applied Mathematics and Computer Science

The paper considers a set membership joint estimation of variables and parameters in complex dynamic networks based on parametric uncertain models and limited hard measurements. A recursive estimation algorithm with a moving measurement window is derived that is suitable for on-line network monitoring. The window allows stabilising the classic recursive estimation algorithm and significantly improves estimate tightness. The estimator is validated on a case study regarding a water distribution network....

Data-driven models for fault detection using kernel PCA: A water distribution system case study

Adam Nowicki;  Michał Grochowski;  Kazimierz Duzinkiewicz — 2012

International Journal of Applied Mathematics and Computer Science

Kernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection. A systematic description of the system's framework is followed by...

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