Ιδρυματικό Αποθετήριο
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Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/2FCC6232-9E01-4327-941B-91B819C5AF2F | - |
| Αναγνωριστικό | https://doi.org/10.1007/978-3-540-74553-2_22 | - |
| Γλώσσα | en | - |
| Μέγεθος | 10 pages | en |
| Τίτλος | A hybrid particle swarm optimization algorithm for clustering analysis | en |
| Δημιουργός | Matsatsinis Nikolaos | en |
| Δημιουργός | Ματσατσινης Νικολαος | el |
| Δημιουργός | Marinakis Ioannis | en |
| Δημιουργός | Μαρινακης Ιωαννης | el |
| Δημιουργός | Marinaki Magdalini | en |
| Δημιουργός | Μαρινακη Μαγδαληνη | el |
| Εκδότης | Springer | en |
| Περίληψη | Clustering is a very important problem that has been addressed in many contexts and by researchers in many disciplines. This paper presents a new stochastic nature inspired methodology, which is based on the concepts of Particle Swarm Optimization (PSO) and Greedy Randomized Adaptive Search Procedure (GRASP), for optimally clustering N objects into K clusters. The proposed algorithm (Hybrid PSO-GRASP) for the solution of the clustering problem is a two phase algorithm which combines a PSO algorithm for the solution of the feature selection problem and a GRASP for the solution of the clustering problem. Due to the nature of stochastic and population-based search, the proposed algorithm can overcome the drawbacks of traditional clustering methods. Its performance is compared with other popular stochastic/metaheuristic methods like genetic algorithms and tabu search. Results from the application of the methodology to a survey data base coming from the Paris olive oil market and to data sets from the UCI Machine Learning Repository are presented. | en |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2015-11-03 | - |
| Ημερομηνία Δημοσίευσης | 2007 | - |
| Θεματική Κατηγορία | Clustering Analysis | en |
| Βιβλιογραφική Αναφορά | Y. Marinakis, M. Marinaki, N. Matsatsinis ,"A hybrid particle Swarm optimization algorithm for clustering analysis,"in 2007 9th Intern. Conf. (DaWaK),pp.241-250.doi:10.1007/978-3-540-74553-2_22 | en |
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