2021
DOI: 10.1007/978-981-16-0733-2_32
|View full text |Cite
|
Sign up to set email alerts
|

Comparative Analysis of Intelligent Solutions Searching Algorithms of Particle Swarm Optimization and Ant Colony Optimization for Artificial Neural Networks Target Dataset

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 17 publications
0
1
0
Order By: Relevance
“…• Ant Colony Optimization-Recent Variants, Applications, and Perspectives: The work of Misra & Chakraborty (2024) offers an exhaustive examination of Ant Colony Optimization (ACO) algorithms and their deployment across a spectrum of engineering challenges [Alfa et al, 2021, Alfa et al, 2020. The authors elucidate the probabilistic essence of ACO, a process wherein artificial ants alter pheromone trails, thereby steering subsequent ants towards superior solutions.…”
Section: Data Colony Optimization (Dco)mentioning
confidence: 99%
“…• Ant Colony Optimization-Recent Variants, Applications, and Perspectives: The work of Misra & Chakraborty (2024) offers an exhaustive examination of Ant Colony Optimization (ACO) algorithms and their deployment across a spectrum of engineering challenges [Alfa et al, 2021, Alfa et al, 2020. The authors elucidate the probabilistic essence of ACO, a process wherein artificial ants alter pheromone trails, thereby steering subsequent ants towards superior solutions.…”
Section: Data Colony Optimization (Dco)mentioning
confidence: 99%