ARTIFICIAL NEURAL NETWORK: A MODULAR APPROACH

被引：0

作者：

Castro, Catarina F. ^{[1
,2
]}

机构：

[1] Univ Porto, Fac Engn, INEGI, Rua Campo Alegre 823, P-4100 Oporto, Portugal

[2] Univ Porto, Fac Engn, DEMec, P-4100 Oporto, Portugal

来源：

M2D2015: PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON MECHANICS AND MATERIALS IN DESIGN | 2015年

关键词：

artificial neural network; modular approach; optimization; complex analysis;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Artificial neural networks (ANNs) are computational performers which can be trained based on a set of examples. ANNs are powerful tools for modeling the highly nonlinear behavior of physiological data. A modular approach gives the possibility of incorporating knowledge into the modelling process through the use of a modular architecture that takes into account the existence of various regimes. The case study presented here addresses flow division in large vessel bifurcations.

引用

页码：2213 / 2214

页数：2

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