Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2005, 149(2):221-224 | DOI: 10.5507/bp.2005.030

WHAT ARE ARTIFICIAL NEURAL NETWORKS AND WHAT THEY CAN DO?

Vlastimil Dohnal^a, Kamil Kuča^b, Daniel Jun^b

^a Department of Food Technology, Faculty of Agronomy, Mendel University of Agriculture and Forestry, Brno, Czech Republic

^b Department of Toxicology, Faculty of Military Health Sciences, University of Defence, Hradec Králové, Czech Republic

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.

Keywords: Artificial neural networks, QSAR, Expert systems

Received: June 10, 2005; Accepted: September 25, 2005; Published: December 1, 2005  Show citation