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Working Temperature Predication of Artificial Heart Based on Neural Network / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation ; (6): 87-112, 2015.
Artigo em Chinês | WPRIM | ID: wpr-310267
ABSTRACT
The purpose of this paper is to achieve a measurement of temperature prediction for artificial heart without sensor, for which the research briefly describes the application of back propagation neural network as well as the optimized, by genetic algorithm, BP network. Owing to the limit of environment after the artificial heart implanted, detectable parameters out of body are taken advantage of to predict the working temperature of the pump. Lastly, contrast is made to demonstrate the prediction result between BP neural network and genetically optimized BP network, by which indicates that the probability is 1.84% with the margin of error more than 1%.
Assuntos
Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Assunto principal: Temperatura / Redes Neurais de Computação / Coração Artificial Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: Chinese Journal of Medical Instrumentation Ano de publicação: 2015 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Assunto principal: Temperatura / Redes Neurais de Computação / Coração Artificial Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: Chinese Journal of Medical Instrumentation Ano de publicação: 2015 Tipo de documento: Artigo