Fault diagnosis and prognosis of wastewater processes with incomplete data by the auto-associative neural networks and ARMA model-Reference-Cited by-同舟云学术

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Fault diagnosis and prognosis of wastewater processes with incomplete data by the auto-associative neural networks and ARMA model

Published:2017-02 Issue: Volume:161 Page:96-107
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Xiao Hongjun,Huang Daoping,Pan Yongping,Liu Yiqi,Song Kang

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Science and Technology Planning Project of Guangdong Province

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference44 articles.

1. ICA and me – a subjective review;Olsson;Water Res.,2012

2. Integrated monitoring, control and security of critical infrastructure systems;Brdys;Annu. Rev. Control,2014

3. A review of process fault detection and diagnosis: part III: process history based methods;Venkatasubramanian;Comput. Chem. Eng.,2003

4. Statistical signal processing approaches to fault detection;Gustafsson;Annu. Rev. Control,2007

5. Sensor fault identification based on time-lagged PCA in dynamic processes;Lee;Chemom. Intell. Lab. Syst.,2004

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