Adam Nowicki - Publications - Bridge of Knowledge

Adam Nowicki

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Year 2012

Data-driven models for fault detection using kernel pca:a water distribution system case study
Publication
- International Journal of Applied Mathematics and Computer Science - Year 2012
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....

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Year 2011

Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
Publication
- A. Nowicki
- M. Grochowski
- LECTURE NOTES IN COMPUTER SCIENCE - Year 2011
Monitoring plays an important role in advanced control of complex dynamic systems. Precise information about system's behaviour, including faults detection, enables efficient control. Proposed method- Kernel Principal Component Analysis (KPCA), a representative of machine learning, skilfully takes full advantage of the well known PCA method and extends its application to nonlinear case. The paper explains the general idea of KPCA...

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