Model of Optimal Centroids Approach for Multivariate Data Classification
Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. 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....
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| Main Authors: | , |
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| Định dạng: | Bài báo |
| Ngôn ngữ: | English |
| Xuất bản : |
Trường Đại học Văn Hóa Hà Nội
2023
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| Chủ đề: | |
| Truy cập trực tuyến: | https://dlic.huc.edu.vn/handle/HUC/3989 |
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Thêm từ khóa | Tóm tắt: | Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. 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. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOS general mathematical model (MPSO) is analyzed as a universal optimization model. 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 /