Application of Adaptive Resonance Theory neural networks to monitor solar hot water systems and detect existing or developing faults

Author:

He Hongbo,Caudell Thomas P.,Menicucci David F.,Mammoli Andrea A.

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference29 articles.

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3. Caudell, T., Newman, D., 1993. An adaptive resonance architecture to define normality and detect novelties in time series and databases. In: Proceedings of the INNS World Congress on Neural Networks, vol. IV, Portlan, Oregon, pp. 166–176.

4. NIRS: large scale ART-1 neural architectures for engineering design retrieval;Caudell;Neural Networks,1994

5. de Keizer, A., Vajen, K., Jordan, U., 2008. Monitoring and failure detection for large scale solar thermal systems: a simulation based approach. Proceedings Gleisdorf Solar 3 (5.9), 2008.

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