摘要
本文采用误差反传播算法,探讨了 Minsky 神经网络用于化学知识表达与处理的可行性。通过几个实例的研究表明:用神经网络方法能较好地处理一些多因子,多类和非线性问题,这种方法将知识和推理结合在一起并具有自学习能力。在化学专家系统的研究中,这将是一种有发展前途的方法。
By means of back-propagation training algorithm,the Minsky neural net has been
used to represent the chemical knowledge.In this work several examples have been studied
and the result demonstrated that neural net can be used to solve some multi-class,
multi-factor and nonlinear problems.By this method the knowledge and infernce engine
are combined and the system has self-study ability.It will be a promising method in the
study of chemical expert system.
出处
《计算机与应用化学》
CAS
CSCD
1991年第4期241-246,共6页
Computers and Applied Chemistry
基金
国家自然科学基金
关键词
神经网络
专家系统
化学
知识表达
Neural net
Expert system
The representation of chemical knowledge
