- Tytuł:
- Suitability assessment of artificial neural network to approximate surface subsidence due to rock mass drainage
- Autorzy:
-
Hejmanowski, R.
Witkowska, H. - Powiązania:
- https://bibliotekanauki.pl/articles/92051.pdf
- Data publikacji:
- 2015
- Wydawca:
- Główny Instytut Górnictwa
- Tematy:
-
osiadanie
odwodnienie kopalni podziemnej
sztuczna sieć neuronowa
MLP
subsidence
drainage of underground mine
artificial neural networks - Opis:
- Based on the previous studies conducted by the authors, a new approach was proposed, namely the tools of artificial intelligence. One of neural networks is a multilayer perceptron network (MLP), which has already found applications in many fields of science. Sequentially, a series of calculations was made for different MLP neural network configuration and the best of them was selected. Mean square error (MSE) and the correlation coefficient R were adopted as the selection criterion for the optimal network. The obtained results were characterized with a considerable dispersion. With an increase in the amount of hidden neurons, the MSE of the network increased while the correlation coefficient R decreased. Similar conclusions were drawn for the network with a small number of hidden neurons. The analysis allowed to select a network composed of 24 neurons as the best one for the issue under question. The obtained final answers of artificial neural network were presented in a histogram as differences between the calculated and expected value.
- Źródło:
-
Journal of Sustainable Mining; 2015, 14, 2; 101-107
2300-1364
2300-3960 - Pojawia się w:
- Journal of Sustainable Mining
- Dostawca treści:
- Biblioteka Nauki
Artykuł