Physics without laws - Making exact predictions with data based methods

被引：3
|
作者：
Kindermann, L
Protzel, P
机构：
来源：
PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年
关键词：
D O I：
10.1109/IJCNN.2002.1007769
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The mathematical method of fractional or continuous iteration can be used to model a dynamical system exactly from limited experimental data. However, mathematics is complicated and exact solutions - even if proven to exist - can rarely be found analytically. We have shown previously that neural networks can be utilized to numerically compute fractional iterates of mathematical functions. In this paper we demonstrate the application of this method to the fundamental experiment of physics: The free fall.
引用
收藏
页码：1673 / 1677
页数：3
相关论文
共 50 条
12345