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Cost-sensitive and sequential feature selection for chiller fault detection and diagnosis

  • Published:2018-02 Issue: Volume:86 Page:401-409
  • ISSN:0140-7007
  • Container-title:International Journal of Refrigeration
  • language:en
  • Short-container-title:International Journal of Refrigeration

Author:

Yan KeORCID,Ma Lulu,Dai Yuting,Shen Wen,Ji Zhiwei,Xie Dongqing

Funder

National Science Foundation of China

science and technology planning key projects of guangdong

talent start-up

Masdar Institute of Science and Technology, Abu Dhabi, UAE

ASHRAE project

Publisher

Elsevier BV

Subject

Mechanical Engineering,Building and Construction

Reference29 articles.

1. Cost sensitive ranking support vector machine for multi-label data learning;Cao,2016

2. A survey on feature selection methods;Chandrashekar;Comput. Electr. Eng.,2014

3. LIBSVM: a library for support vector machines;Chang;ACM Trans. Intell. Syst. Technol. (TIST),2011

4. Experimental Data From Fault Detection and Diagnostic Studies on a Centrifugal Chiller;Comstock,1999

5. Machine learning for sequential data: A review;Dietterich,2002
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