Dynamic Multi-Swarm Differential Learning Quantum Bird Swarm Algorithm and Its Application in Random Forest Classification Model
Bird swarm algorithm is one of the swarm intelligence algorithms proposed recently. However, the original bird swarm algorithm has some drawbacks, such as easy to fall into local optimum and slow convergence speed. To overcome these short-comings, a dynamic multi-swarm differential learning quantum...
Main Authors: | Jiangnan Zhang, Kewen Xia, Ziping He, Shurui Fan |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2020/6858541 |
Similar Items
-
Solving Multi-Objective Problems Using Bird Swarm Algorithm
by: Essam H. Houssein, et al.
Published: (2021-01-01) -
Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm
by: Dong Yumin, et al.
Published: (2014-01-01) -
A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization
by: Tao Sun, et al.
Published: (2017-01-01) -
Improved Quantum Particle Swarm Optimization for Mangroves Classification
by: Zhehuang Huang
Published: (2016-01-01) -
Dynamic Multi-Swarm Particle Swarm Optimization Based on Elite Learning
by: Xuewen Xia, et al.
Published: (2019-01-01)