摘要
岩体质量评价问题可以认为是一个模式识别或分类问题。人工神经网络具有表达任意非线性映射的特性，从而在分类、学习和容错方面表现了较好的能力。本文结合岩体质量的模式识别，阐述了半线性前馈神经网络的基本原理和应用，并给出了其部分试验结果。
The rock quality evaluation can be taken as a pattern recognition or classification problem.The artificial neural network has the character of express arbitrary nonlinear mapping, thus, it works very well in operating classification and learning, and its tolerant errors as well. In this paper, the principle and application of semilinear feedforward neural network are described, some experimental results are also presented.
出处
《武汉化工学院学报》
1994年第3期62-65,共4页
Journal of Wuhan Institute of Chemical Technology
关键词
岩体质量评价
神经网络
模式识别
ock quality evaluation
Neural network
Pattern recognition
