Dohnal Vlastimil, Kuca Kamil, Jun Daniel
Department of Food Technology, Mendel University of Agriculture and Forestry, Brno, Czech Republic.
Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2005 Dec;149(2):221-4. doi: 10.5507/bp.2005.030.
The artificial neural networks (ANN) are very often applied in many areas of toxicology for the solving of complex problems, such as the prediction of chemical compound properties and quantitative structure-activity relationship. The aim of this contribution is to give the basic knowledge about conception of ANN, theirs division and finally, the typical application of ANN will be discussed. Due to the diversity of architectures and adaptation algorithms, the ANNs are used in the broad spectrum of applications from the environmental processes modeling, through the optimization to quantitative structure-activity relationship (QSAR) methods. In addition, especially ANNs with Kohonen learning are very effective classification tool. The ANNs are mostly applied in cases, where the commonly used methods does not work.
人工神经网络（ANN）经常应用于毒理学的许多领域，以解决复杂问题，如预测化合物性质和定量构效关系。本文的目的是提供关于人工神经网络概念、其分类的基本知识，最后将讨论人工神经网络的典型应用。由于架构和自适应算法的多样性，人工神经网络被广泛应用于从环境过程建模、优化到定量构效关系（QSAR）方法等广泛的应用领域。此外，特别是具有Kohonen学习的人工神经网络是非常有效的分类工具。人工神经网络大多应用于常用方法不起作用的情况。
