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Temperature models of a homogeneous medium under therapeutic ultrasound
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Orientador(es)
Resumo(s)
Temperature modelling of human tissue subjected to ultrasound for therapeutic use is essential for an accurate instrumental assessment and calibration. Prior studies developed on a homogeneous medium are hereby reported. Non-linear punctual temperature modelling is proposed by means of Radial Basis Functions Neural Network (RBFNN) structures. The best-performed structures are obtained using a Multiobjective Genetic Algorithm (MOGA). The best performed neural structure presents a Root Mean Square Error (RMSE) of one order magnitude less than the one presented by the best behaved linear model - the AutoRegressive with eXogenous inputs (ARX); The maximum absolute error achieved with the neural model was 0.2 ºC.
Descrição
Palavras-chave
Temperature modelling Neural networks Multi-objective genetic algorithms Ultrasound
Contexto Educativo
Citação
Teixeira, C. A.; Cortela, G.; Gomez, H.; Ruano, M. G.; Ruano, A. E.; Negreira, C.; Pereira, W. C. A. Temperature models of a homogeneous medium under therapeutic ultrasound, Revista Brasileira de Engenharia Biomédica, 20, 2-3, 97-101, 2004.