首页> 外文会议>ASME international design engineering technical conferences and computers and information in engineering conference 2011.;vol. 2 pt. A. >DEFORMATION PREDICTION OF MOUSE EMBRYOS IN CELL INJECTION EXPERIMENT BY A FEEDFORWARD ARTIFICIAL NEURAL NETWORK
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DEFORMATION PREDICTION OF MOUSE EMBRYOS IN CELL INJECTION EXPERIMENT BY A FEEDFORWARD ARTIFICIAL NEURAL NETWORK

机译:前馈人工神经网络预测细胞注射实验中小鼠胚胎的形变

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In this study, neural network models have been used to predict the mechanical behaviors of mouse embryos. 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. In order to reach these purposes two neural network models have been implemented. Experimental data earlier deduced-by [Flueckiger, M. (2004) Cell Membrane Mechanical Modeling for Microrobotic Cell Manipulation. Diploma Thesis, ETHZ Swiss Federal Institute of Technology, Zurich, WS03/04] -were collected to obtain training and test data for the neural network. The results of these investigations show that the correlation values of the test and training data sets are between0.9988 and 1.0000, which are in good agreement with the experimental observations.
机译:在这项研究中,神经网络模型已用于预测小鼠胚胎的机械行为。此外,已经进行了敏感性分析,以研究输入参数的重要性对小鼠胚胎机械行为的影响。为了达到这些目的,已经实现了两个神经网络模型。 [Flueckiger,M。(2004)细胞膜机械建模用于微机器人细胞操纵的早期推导的实验数据。 ETHZ瑞士联邦理工学院,苏黎世,WS03 / 04]的文凭论文被收集以获得神经网络的训练和测试数据。这些调查的结果表明,测试和训练数据集的相关值在0.9988和1.0000之间,与实验观察结果非常吻合。

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