An artificial immune and incremental learning inspired novel framework for performance pattern identification of complex electromechanical systems-Reference-Cited by-同舟云学术

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An artificial immune and incremental learning inspired novel framework for performance pattern identification of complex electromechanical systems

Published:2019-07-08 Issue:1 Volume:63 Page:1-13
ISSN:1674-7321
Container-title:Science China Technological Sciences
language:en
Short-container-title:Sci. China Technol. Sci.

Author:

Wang RongXi,Gao Xu,Gao JianMin,Gao ZhiYong,Chen Kun,Peng CaiYuan

Publisher

Springer Science and Business Media LLC

Subject

General Engineering,General Materials Science

Link

http://link.springer.com/content/pdf/10.1007/s11431-019-9532-5.pdf

Reference53 articles.

1. Wang R X, Gao J M, Gao Z Y, et al. Complex network theory-based condition recognition of electromechanical system in process industry. Sci China Tech Sci, 2016, 59: 604–617

2. Jiang H, Wang R, Gao J, et al. Evidence fusion-based framework for condition evaluation of complex electromechanical system in process industry. Knowledge-Based Syst, 2017, 124: 176–187

3. Wang R, Gao X, Gao J, et al. An information transfer based novel framework for fault root cause tracing of complex electromechanical systems in the processing industry. Mech Syst Signal Pr, 2018, 101: 121–139

4. Chen Q, Whitbrook A, Aickelin U, et al. Data classification using the Dempster-Shafer method. J Exp Theor Artif In, 2014, 26: 493–517

5. Kumar P M, Lokesh S, Varatharajan R, et al. Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier. Future Generation Comput Syst, 2018, 86: 527–534

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