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Aug 15, 2012 · In this study, we have offered an elegant method to deal with high complexity of game theoretic multi-objective clustering methods in large- ...
In this study, we have offered an elegant method to deal with high complexity of game theoretic multi-objective clustering methods in large-sized data sets.
This study has offered an elegant method to deal with high complexity of game theoretic multi-objective clustering methods in large-sized data sets using a ...
In this study, we have offered an elegant method to deal with high complexity of game theoretic multi-objective clustering methods in large-sized data sets.
Automatic multi-objective clustering based on game theory
www.sciencedirect.com › article › abs › pii
In this paper, we propose a sequential game theoretic approach for multi-objective clustering, called ClusSMOG-II.
A Novel Strategy Selection Method for Multi-Objective Clustering Algorithms Using Game Theory. M Badami, A Hamzeh, S Hashemi. arXiv preprint arXiv:1208.3432 ...
Novel multi-objective clustering algorithm based-sequential games was proposed.It optimizes simultaneously and efficiently multiple conflicting objectives.
Missing: Strategy | Show results with:Strategy
The approach consists of three main steps. The first step sets initial clusters with their representatives, whereas the second step calculates the correct ...
In this study, we have offered an elegant method to deal with high complexity of game theoretic multi-objective clustering methods in large-sized data sets.
7 days ago · This paper proposes a novel clustering control scheme based on fuzzy logic and Nash equilibrium to enhance scalability, network stability, and ...