Model of optimal centroids approach for multivariate data classification
Abstract-Particle swarm optimization (PSO) is a population- based stochastic optimization algorithm proposed for the first time by Kennedy et al. in 1994. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimizat...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://dlic.huc.edu.vn/handle/HUC/3974 |
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Add Tag | Summary: | Abstract-Particle swarm optimization (PSO) is a population- based stochastic optimization algorithm proposed for the first time by Kennedy et al. in 1994. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO's ideas are simple and easy to understand but PSO is only applied in simple model problems. Until now, the official mathematical model of PSO has not been presented. In this paper, will be re-present as a general mathematical model and apply in the multivariate data classification. First, PSO's the general mathematical model (MPSO) is analyzed so that can be applied into complex application models. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes. |
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Artificial intelligence and soft computing : behavioral and cognitive modeling of the human brain /