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Deformation prediction by a feed forward artificial neural network during mouse embryo micromanipulation

Animal Cells and Systems 2012년 16권 2호 p.121 ~ 126
Abbasi Ali A., Vossoughi G. R., Ahmadian M. T.,
소속 상세정보
 ( Abbasi Ali A. ) - Sharif University of Technology School of Mechanical Engineering
 ( Vossoughi G. R. ) - Sharif University of Technology School of Mechanical Engineering
 ( Ahmadian M. T. ) - Sharif University of Technology School of Mechanical Engineering

Abstract


In this study, a neural network (NN) modeling approach has been used to predict the mechanical and geometrical behaviors of mouse embryo cells. Two NN models have been implemented. In the first NN model dimple depth (w), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were used as inputs of the model while indentation force (f) was considered as output. In the second NN model, indentation force (f), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were considered as inputs of the model and dimple depth was predicted as the output of the model. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. Experimental data deduced by Fluckiger (2004) were collected to obtain training and test data for the NN. The results of these investigations show that the correlation values of the test and training data sets are between 0.9988 and 1.0000, and are in good agreement with the experimental observations.

키워드

artificial neural network; biological cells; error back propagation algorithm; sensitivity analysis

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