首页 /研究 /Using Artificial Neural Networks for Solving Engineering Problems
LEARNING

Using Artificial Neural Networks for Solving Engineering Problems

Y. F. Lou, Paul Brunn

发表年份
1995
引用次数
3

摘要

SummaryAn artificial neural network (ANN) is a ‘black box’ capable of learning and reproducing a relationship between its inputs and outputs. Once trained, ANNs can calculate a set of outputs very quickly and it is this speed of computing that encourages their application in practical problems, in particular, the inverse kinematic problem for a two-link robot arm. Characteristics such as accuracy and the effects of network and training set size are discussed. Network accuracy is improved by an iterative process and thus becomes a practical solution for this problem. In general, without careful design ANN methods can have large errors that can cause their application to fail.

关键词

Artificial neural networkComputer scienceSet (abstract data type)Inverse kinematicsProcess (computing)Artificial intelligenceBlack boxInverseRobotMathematics

相关论文

查看 LEARNING 分类全部论文