- Tytuł:
- Predicting Young’s modulus of Indian coal measure rock using multiple regression and artificial neutral network
- Autorzy:
-
Chakraborty, Sayantan
Bisai, Rohan
Roy, Rohit
Palaniappan, Sathish Kumar
Pal, Samir Kumar
Rao, Karanam Uma Maheshwar - Powiązania:
- https://bibliotekanauki.pl/articles/2201429.pdf
- Data publikacji:
- 2023
- Wydawca:
- Główny Instytut Górnictwa
- Tematy:
-
sandstone
shale
multiple regression
outlier analysis
artificial neural network
piaskowiec
łupek ilasty
regresja wielokrotna
analiza odchyleń
sztuczna sieć neuronowa - Opis:
- Accurate information on Young’s modulus (E) is required for simulating rock deformation in mines; on the other hand, it is very cumbersome to obtain in the laboratory and collecting drilled cores in sufficient amounts, especially in the case of soft rocks, is quite impossible. Empirical equations were deducted for - from easily determinable rock properties, and the final model was selected through different statistical strength parameter tests. The generalization of the equation was verified through the normal distribution tests of residues of the equation. R2 came to be 0.609 and was validated using an artificial neural network with an improved value of 0.73.
- Źródło:
-
Journal of Sustainable Mining; 2023, 22, 1; 41--54
2300-1364
2300-3960 - Pojawia się w:
- Journal of Sustainable Mining
- Dostawca treści:
- Biblioteka Nauki
Artykuł