Month: January 2001

Problem of selection of proper architecture for neural network Ryszard Tadeusiewicz AGH University of Science and Technology, al. Adama Mickiewicza 30, 30-059 Kraków. DOI: https://doi.org/10.7494/cmms.2001.1.0001 Abstract: Review of problems connected with applications of artificial neural networks in generally understood metallurgy is discussed in the paper. Conditions, which particular tasks impose on the selection of the … Read more

Selection of neural network structure in real time control systems Krzysztof Kołek, Wojciech Mitkowski AGH University of Science and Technology. DOI: https://doi.org/10.7494/cmms.2001.1.0002 Abstract: In this paper example applications of neural networks for controlling laboratory models are presented. Two structures of neural controllers are considered. The neural networks are applied as neural controllers for three real … Read more

Application of artificial neural networks to classification of quality of ingots after continuous casting Władysław Zalecki AGH University of Science and Technology, al. Adama Mickiewicza 30, 30-059 Kraków. DOI: https://doi.org/10.7494/cmms.2001.1.0003 Abstract: The paper present primary results on an application of artificial neural networks to predictions of the influence of technological parameters of continuous casting on … Read more

Application of artificial neural network to an assessment of influence of residual microalloing elements on mechanical properties of steel products Roman Kuziak1, Władysław Zalecki1, Jan Kusiak2 1Instytut Metalurgii Żelaza, ul. K. Miarki I 2, 44-100 Gliwice. 2AGH University of Science and Technology, al. Adama Mickiewicza 30, 30-059 Kraków. DOI: https://doi.org/10.7494/cmms.2001.1.0004 Abstract: The work presents some … Read more

Identification of the experiment plan for neuron approximation Roma Górecka, Jacek Pietraszek, Zbigniew Polański AGH University of Science and Technology, al. Adama Mickiewicza 30, 30-059 Kraków. DOI: https://doi.org/10.7494/cmms.2001.1.0005 Abstract: The paper describes an application of the SDM method (sequence data modification) to searching for an optimum structure of training data set (experiment plan) in a … Read more