Phase Prediction of Multi-principal Element Alloys Using Machine Learning Methods

Nguyen, Hai Chau and Kubo, Masatoshi and Le, Viet Hai and Yamamoto, Tomoyuki (2021) Phase Prediction of Multi-principal Element Alloys Using Machine Learning Methods. In: 13th Asian Conference on Intelligent Information and Database Systems 2021 (ACIIDS 2021), 7-10 Apr 2021, Phuket, Thailand. (In Press)

Full text not available from this repository.

Abstract

Designing new materials with desired properties is a complex and time consuming process. One of the challenging factors of the design process is the huge search space of possible materials. Machine learning methods such as k-nearest neighbours, support vector machine (SVM) and artificial neural network (ANN) can contribute to this process by accurately predicting materials properties. Properties of multi-principal element alloys (MPEAs) highly depend on alloys’ phases. Thus accurate prediction of alloy’s phase is important to eliminate the search space. In this paper we propose a solution of employing support vector machine method with hyperparameters tuning and the use of weights values for alloy’s phase prediction. Comparative experiments show that on a 118 MPEAs dataset, our solution achieves cross-validation accuracy of 90%. It is 6.7% higher than that of ANN. On another 401 MPEAs dataset, our solution is comparable to ANN and obtains 70.7% cross-validation accuracy.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Title and abstract of the paper will probably changed upon reviewers' recommendation. Latest version will be updated soon.
Subjects:	Information Technology (IT) Engineering Physics
Divisions:	Faculty of Information Technology (FIT)
Depositing User:	Hải Châu Nguyễn
Date Deposited:	18 Dec 2020 09:08
Last Modified:	18 Dec 2020 09:08
URI:	http://eprints.uet.vnu.edu.vn/eprints/id/eprint/4291

Available Versions of this Item

• Phase Prediction of Multi-principal Element Alloys Using Machine Learning Methods. (deposited 11 Dec 2020 01:36)
  • Phase Prediction of Multi-principal Element Alloys Using Machine Learning Methods. (deposited 18 Dec 2020 09:08) [Currently Displayed]
    • Phase Prediction of Multi-principal Element Alloys Using Support Vector Machine and Bayesian Optimization. (deposited 15 Mar 2021 04:23)

Actions (login required)

View Item