Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Archives of Metallurgy and Materials

1 2022

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: metalloid elements

Sortuj według:

Ogranicz wyniki do:

The Prediction of Optimized Metalloid Content in Fe-Si-B-P Amorphous Alloys Using Artificial Intelligence Algorithm

Lee Min_Woo, Choi Young-Sin, Kwon Do-Hun, Cha Eun-Ji, Kang Hee-Bok, Jeong Jae-In, Lee Seok-Jae, Kim Hwi-Jun

Archives of Metallurgy and Materials

2022

Vol. 67, iss. 4

1539--1542

Artificial intelligence operated with machine learning was performed to optimize the amount of metalloid elements (Si, B, and P) subjected to be added to a Fe-based amorphous alloy for enhancement of soft magnetic properties. The effect of metalloid elements on magnetic properties was investigated through correlation analysis. Si and P were investigated as elements that affect saturation magnetization while B was investigated as an element that affect coercivity. The coefficient of determination R2 (coefficient of determination) obtained from regression analysis by learning with the Random Forest Algorithm (RFR) was 0.95 In particular, the R2 value measured after including phase information of the Fe-Si-B-P ribbon increased to 0.98. The optimal range of metalloid addition was predicted through correlation analysis method and machine learning.