Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a novel multi-objective evolutionary clustering approach using variable-length real jumping genes genetic algorithms (VRJGGA). The proposed algorithm that extends jumping genes genetic algorithm (JGGA) (Man et al., 2004) evolves near-optimal clustering solutions using multiple clustering criteria, without a-priori knowledge of the actual number of clusters. Experimental results based on several artificial and real-world data show that VRJGGA can obtain non-dominated and near-optimal clustering solutions in terms of different cluster quality measures and classification performance
['K.S. Nawaz Ripon', 'Chi-Ho Tsang', 'S. Kwong', 'Man-Ki Ip']
I am writing a research paper on a idea Multi-Objective Evolutionary Clustering using Variable-Length Real Jumping Genes Genetic Algorithm
[{"from": "human", "value": "I am writing a research paper on a idea Multi-Objective Evolutionary Clustering using Variable-Length Real Jumping Genes Genetic Algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a novel multi-objective evolutionary clustering approach using variable-length real jumping genes genetic algorithms (VRJGGA). The proposed algorithm that extends jumping genes genetic algorithm (JGGA) (Man et al., 2004) evolves near-optimal clustering solutions using multiple clustering criteria, without a-priori knowledge of the actual number of clusters. Experimental results based on several artificial and real-world data show that VRJGGA can obtain non-dominated and near-optimal clustering solutions in terms of different cluster quality measures and classification performance"}]