计算机应用与软件2025，Vol.42Issue(6)：302-310,9.DOI:10.3969/j.issn.1000-386x.2025.06.040
基于元学习和集成学习的高熵合金相预测算法
A PHASE PREDICTION ALGORITHM OF HIGH ENTROPY ALLOYS BASED ON META-LEARNING AND ENSEMBLE LEARNING
摘要
Abstract
Accurate phase prediction of high entropy alloys is beneficial to reduce the workload of material design and development cycle,and improve the performance of materials.Therefore,a phase prediction algorithm of high entropy alloys based on meta-learning and ensemble learning is proposed.The algorithm consisted of relation mapping model and optimization model.Among them,the former established a mapping relationship the meta-features combined with material knowledge and the performance of the selective ensemble learning to recommend an appropriate ensemble algorithm.The latter adopted artificial bee colony algorithm based on single accuracy constraint to improve the accuracy of ensemble learning.The experimental results show that the prediction performance of this algorithm is better than that of other selective ensemble learning algorithms.关键词
高熵合金/相预测/元学习/集成学习/人工蜂群算法Key words
High entropy alloys/Phase prediction/Meta-learning/Ensemble learning/Artificial bee colony algorithm分类
计算机与自动化引用本文复制引用
侯帅,李玉娇,白梅娟,孙梦玥,石修志..基于元学习和集成学习的高熵合金相预测算法[J].计算机应用与软件,2025,42(6):302-310,9.基金项目
国家自然科学基金项目(52175455) （52175455）
国家重点研究发展项目(2020YFB1709903) （2020YFB1709903）
河北省重点研发计划项目(21350101D). （21350101D）
