A Hybrid Global Optimization Algorithm Based on Particle Swarm Optimization and Gaussian Process
The optimization problems and algorithms are the basics subfield in artificial intelligence, which is booming in the almost any industrial field. However, the computational cost is always the issue which hinders its applicability. This paper proposes a novel hybrid optimization algorithm for solving...
Main Authors: | Yan Zhang, Hongyu Li, Enhe Bao, Lu Zhang, Aiping Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2019-11-01
|
Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://www.atlantis-press.com/article/125921752/view |
Similar Items
-
Dual-Stage Hybrid Learning Particle Swarm Optimization Algorithm for Global Optimization Problems
by: Wei Li, et al.
Published: (2022-12-01) -
Exponential Particle Swarm Optimization for Global Optimization
by: Khelil Kassoul, et al.
Published: (2022-01-01) -
Differential Elite Learning Particle Swarm Optimization for Global Numerical Optimization
by: Qiang Yang, et al.
Published: (2022-04-01) -
A Multi-Objective Particle Swarm Optimization Algorithm Based on Gaussian Mutation and an Improved Learning Strategy
by: Ying Sun, et al.
Published: (2019-02-01) -
A Random Particle Swarm Optimization Based on Cosine Similarity for Global Optimization and Classification Problems
by: Yujia Liu, et al.
Published: (2024-03-01)