Hybrid Firefly and Black Hole Algorithm Designed for XGBoost Tuning Problem: An Application for Intrusion Detection-Reference-Cited by-同舟云学术

Hybrid Firefly and Black Hole Algorithm Designed for XGBoost Tuning Problem: An Application for Intrusion Detection

Published:2023 Issue: Volume:11 Page:28551-28564
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Yong Xin¹^ORCID,Gao Yuelin²^ORCID

Affiliation:

1. School of Computer Science and Engineering, North Minzu University, Ningxia, Yinchuan, China

2. Ningxia Province Key Laboratory of Intelligent Information and Data Processing, North Minzu University, Ningxia, Yinchuan, China

Funder

Key Project of Ningxia Natural Science Foundation

National Natural Science Foundation of China

Construction Project of First-class Subjects in Ningxia Higher Education

Major Proprietary Funded Project of North Minzu University

Basic Discipline Research Projects supported by Nanjing Securities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10077572.pdf?arnumber=10077572

Reference48 articles.

1. Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration

2. A Systematic Review on Firefly Algorithm: Past, Present, and Future

3. A Pedestrian Detection Method Based on Genetic Algorithm for Optimize XGBoost Training Parameters

4. Firefly algorithms for multimodal optimization stochastic algorithms: foundations and applications;yang;Stochastic Algorithms Foundations and Applications,2009

5. A feature selection algorithm for intrusion detection system based on Pigeon Inspired Optimizer

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