摘要
泡沫金属试样测试复杂 ,对试样而言又急需知道基体结构参数与力学性能和阻尼性能的关系 ,采用线性回归技术无法实现这一功能 ,应用人工神经网络 ,则解决了通过测量泡沫金属的四个基本参数达到推知其力学性能、阻尼性能的课题。
It's very complex to test sample of foam metal. But we're eager to know the relationship between structure parameters and mechanics property, damping property. It's hard to fulfil such fraction by linear regression technology because of complexity of foam metal structure. Depending on artificial neural networks, this paper solves to predict mechanics property and damping troperty by measuring four basic parameters of foam metal.
出处
《郑州航空工业管理学院学报（管理科学版）》
2004年第4期43-44,共2页
Journal of Zhengzhou Institute of Aeronautical Industry Management
基金
河南省科技攻关计划 (0 42 42 60 0 0 2 )
关键词
人工神经网络
泡沫金属
粘弹性材料
阻尼
artificial neural netoworks
foam metal
viscoelastic materials
damping
