Generative adversarial network for fault detection diagnosis of chillers

Author:

Yan KeORCID,Chong AdrianORCID,Mo Yuchang

Funder

Ministry of Education (MOE) Singapore, Tier 1 Grant for faculty start-up research in National University of Singapore

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Building and Construction,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering

Reference62 articles.

1. Cross-level fault detection and diagnosis of building HVAC systems;Wu;Build. Environ.,2011

2. U.S. DOE, Buildings Energy Data Book, Energy Efficiency & Renewable Energy Department .

3. Optimized design of low-rise commercial buildings under various climates–Energy performance and passive cooling strategies;Lapisa;Build. Environ.,2018

4. C. Gordon, W. Cheong, C. Marzin, R. Rahmat, reportSingaporeŚecond National Climate Change Study-Climate Projections to 2100-Report to Stakeholders, Centre for Climate Research Singapore, Singapore .

5. Indoor climate experience, migration, and thermal comfort expectation in buildings;Luo;Build. Environ.,2018

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