Fractional-order binary bat algorithm for feature selection on high-dimensional microarray data
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-022-04450-3.pdf
Reference56 articles.
1. Al-Betar MA, Alomari OA, Abu-Romman SM (2020) A TRIZ-inspired bat algorithm for gene selection in cancer classification. Genomics 112:114–126
2. Alomari OA, Khader AT, Al-Betar MA, Abualigah LM (2017) Gene selection for cancer classification by combining minimum redundancy maximum relevancy and bat-inspired algorithm. Int J Data Min Bioinform 19:32–51
3. Alomari OA, Khader AT, Al-Betar MA, Awadallah MA (2018) A novel gene selection method using modified MRMR and hybrid bat-inspired algorithm with β-hill climbing. Appl Intell 48:4429–4447
4. Annavarapu CSR, Dara S (2021) Clustering-based hybrid feature selection approach for high dimensional microarray data. Chemom Intell Lab Syst 213:104305
5. Caponetto R (2010) Fractional order systems: modeling and control applications. World Scientific, Singapore
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A hybrid intelligent optimization algorithm to select discriminative genes from large-scale medical data;International Journal of Machine Learning and Cybernetics;2024-09-05
2. A Multi-Strategy Improved Golden Jackal Optimization Algorithm Integrating the Golden Sine Mechanism;Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy;2024-03
3. Gene selection for high dimensional biological datasets using hybrid island binary artificial bee colony with chaos game optimization;Artificial Intelligence Review;2024-02-13
4. Feature Subset Selection for High-Dimensional, Low Sampling Size Data Classification Using Ensemble Feature Selection With a Wrapper-Based Search;IEEE Access;2024
5. A scalable memory-enhanced swarm intelligence optimization method: fractional-order Bat-inspired algorithm;International Journal of Machine Learning and Cybernetics;2023-12-11
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3