A Developmental Study of the Free-formed Surface System Using the Neural Networks

使用神经网络的自由曲面系统的发展研究

• 批准号: 03555028
• 负责人: FURUKAWA Masashi
• 金额: $ 0.77万
• 依托单位: Asahikawa National College of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Developmental Scientific Research (B)
• 财政年份: 1991
• 资助国家: 日本
• 起止时间: 1991 至 1992
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-03555028/
• 关键词: Free-formed Surface; Free-formed Curve; Neural Networks; Back Propagation Method; Brawn Surface; Learning; CAGD; Surface Interpolation; 最適化; 曲面設計; ニュ-ラル・ネットワ-ク; 情報量基準; Brown曲面

The first purpose of this research is to determine parameters of Brown surface, which can handle the surface features with the use of tension and bias control procedures. The back propagation method, one of the neural networks, is employed for determining the control values. The feature of surface have their related control values. These values are learned by the neural networks, and they are applied to surface control after leaning. The five layers back propagation method is implemented. Experimental surface designs show that this attempt introduces good results into surface designing.In investigating properties of the back propagation method, it is noticed that the back propagation method itself has the interpolation functions. This means that the back propagation method with 5 layers is able to be directly used for interpolating and designing the surfaces. In order to make sure of these properties, numerical experiments are attempted to collect their behaviors for making use of free-formed curves interpolation. It give us a good result as a curve fitting. In near future, it is planed to apply this result to design free-formed surface.

本研究的第一个目的是确定布朗表面的参数，该参数可以使用张力和偏置控制程序来处理表面特征。采用神经网络之一的反向传播方法来确定控制值。表面的特征有其相关的控制值。这些值由神经网络学习，并在倾斜后应用于表面控制。实现了五层反向传播方法。实验表面设计表明，这种尝试为表面设计带来了良好的结果。在研究反向传播方法的性质时，注意到反向传播方法本身具有插值函数。这意味着5层的反向传播方法可以直接用于曲面的插值和设计。为了确保这些特性，尝试通过数值实验来收集它们的行为，以利用自由曲线插值。它为我们提供了良好的曲线拟合结果。在不久的将来，计划将这一结果应用于自由曲面的设计。