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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Articles in this Issue were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on as a courtesy and upon agreement with the previous journal publisher.
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Math. Comput. Appl. 2011, 16(3), 702-711;

Simulation of Hemodynamics in a Graft-To-Vein Anastomoses by Adaptive Neuro-Fuzzy Based Modeling

Department of Genetics and Bioengineering, Turkey
Department of Environmental Engineering Fatih University, Büyükçekmece, 34500, Istanbul, Turkey
Author to whom correspondence should be addressed.
Published: 1 December 2011
PDF [251 KB, uploaded 24 March 2016]


A new methodology for simulating the flow field inside an arteriovenous (AV) graft to vein anastomoses by the adaptive neuro fuzzy inference system (ANFIS) is presented in this study. For determining the optimal AV graft angle, an ANFIS-based model of neuro fuzzy-graft-vein (NF-GVEIN) is proposed. Therefore engineering design of the graft can be supported. The advantage of this neuro-fuzzy hybrid model is that it does not require the model structure to be known a priori, in contrast to most of the modeling techniques. A case study with real experimental data was carried out. NFGVEIN was optimized by means of selection of the algorithm among 34 ANFIS algorithms by terms of minimal error. The optimal neural network structure was determined. The optimal AV graft angle causing the least turbulence was obtained. The simulation results showed that this model is feasible for forecasting of finding the optimal AV graft angle inside AV graft to vein anastomoses with different flow rates.
Keywords: Neural Networks; ANFIS; Hemodynamics; Graft Design Neural Networks; ANFIS; Hemodynamics; Graft Design
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Arslan, N.; Karaca, F. Simulation of Hemodynamics in a Graft-To-Vein Anastomoses by Adaptive Neuro-Fuzzy Based Modeling. Math. Comput. Appl. 2011, 16, 702-711.

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