Multi-strategy ensemble binary hunger games search for feature selection-Reference-Cited by-同舟云学术

Multi-strategy ensemble binary hunger games search for feature selection

Published:2022-07 Issue: Volume:248 Page:108787
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Ma Benedict Jun^ORCID,Liu Shuai,Heidari Ali Asghar

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference86 articles.

1. Machine learning: Trends, perspectives, and prospects;Jordan;Science,2015

2. The first step towards intelligent wire arc additive manufacturing: An automatic bead modelling system using machine learning through industrial information integration;Ding;J. Ind. Inf. Integr.,2021

3. Improving the accuracy of medical diagnosis with causal machine learning;Richens;Nature Commun.,2020

4. Exploring the financial indicators to improve the pattern recognition of economic data based on machine learning;Wei;Neural Comput. Appl.,2021

5. BEPO: A novel binary emperor penguin optimizer for automatic feature selection;Dhiman;Knowl.-Based Syst.,2021

Cited by 41 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. An accurate estimation of hand gestures using optimal modified convolutional neural network;Expert Systems with Applications;2024-09

2. Golden lichtenberg algorithm: a fibonacci sequence approach applied to feature selection;Neural Computing and Applications;2024-08-13

3. Optimizing feedforward neural networks using a modified weighted mean of vectors: Case study chemical datasets;Swarm and Evolutionary Computation;2024-08

4. An improved multi-strategy Golden Jackal algorithm for real world engineering problems;Knowledge-Based Systems;2024-07

5. Enhancing network security with information-guided-enhanced Runge Kutta feature selection for intrusion detection;Cluster Computing;2024-06-15