Group method of data handling and neural networks applied in temperature sensors monitoring

Autor:	Iraci Martinez Pereira, Elaine Inacio Bueno, Antonio Teixeira e Silva
Rok vydání:	2011
Předmět:	Data processing Temperature monitoring Artificial neural network Computer science Group method of data handling business.industry Research reactor Monitoring system Control engineering Artificial intelligence business Massively parallel
Zdroj:	International Journal of Nuclear Knowledge Management. 5:260
ISSN:	1479-5418 1479-540X
DOI:	10.1504/ijnkm.2011.042003
Popis:	In this work a monitoring system is developed based on the Group Method of Data Handling (GMDH) and Artificial Neural Networks (ANNs) methodologies. GMDH creates non-linear algebraic models for system characterisation and ANN is a massively parallel distributed processor made up of simple processing units called neurons. The monitoring system was applied to the IEA-R1 research reactor at Instituto de Pesquisas Energeticas e Nucleares (IPEN) by using a database obtained from a theoretical model of the reactor. The IEA-R1 research reactor is a pool-type reactor of 5 MW cooled and moderated by light water, and uses graphite and beryllium as reflector. The two methodologies (GMDH and ANN) were combined to develop a temperature monitoring system. The results were compared with previous works where GMDH and ANN were used separately and the results obtained showed an improved monitoring system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0157b07418e76d6c17c6367a004f42c3 https://doi.org/10.1504/ijnkm.2011.042003 Zobrazit plný text záznamu