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| A Genetic Algorithms Based Mercer Kernel Clustering Method |
| ZHOU LinFeng1 , DING YongSheng2, 3 |
1.College of Computer Sciences and Technology, Donghua University, Shanghai 201620
2.College of Information Sciences and Technology, Donghua University, Shanghai 201620
3.Engineering Research Center of Digitized Textile and Fashion Technology,
Donghua University, Shanghai 201620 |
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Abstract Based on Mercer kernel function theorem and genetic algorithms, a novel genetic algorithms based mercer kernel clustering method is proposed. Using Mercer kernel function, an elegant way to map the input space nonlinearly to the high dimensional feature space is gotten, which manifests the feature differences of samples, so that it not only gets more accurate clustering results but also speeds up the convergence rate of the algorithm. And, integrated with genetic algorithm, it can overcome the problem of local minima. Simulation experiments and an application to the objective evaluation of textile products verify its feasibility and effectiveness.
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Received: 01 June 2005
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2006, Vol. 19 
