Abstract: This paper introduces a general approach based on genetic algorithms for optimizing a broad class of clustering criteria.
Abstract. This paper introduces a general approach based on genetic algorithms for optimizing a broad class of clustering criteria.
This paper introduces a general approach based on genetic algorithms for optimizing a broad class of clustering criteria which re-parameterizes the criteria ...
Abstract—Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling ...
Optimization methods used to realization of this paper were genetic algorithms and for selection method roulette wheel method is used. Keywords cluster center, ...
Missing: Criteria | Show results with:Criteria
The purpose of this paper is to address the decrease in GA-based instance selection performance for regression tasks caused by the dataset size increase.
Aug 26, 2011 · Thus the improved performance of the FVGA-clustering technique can be attributed to the use of both genetic search and the optimizing criterion.
This study combines FCM with Genetic Algorithm, GA, Subtractive Clustering, SC, and Bayesian cluster validation for a novel clustering method, fzGASCE
Oct 1, 2023 · The proposed algorithm is more powerful and efficient than other algorithms and, hence, can be used to effectively cluster large data sets.
We have developed a genetic approach for the optimization of the clustering criterion in the fuzzy c-means algorithm. The proposed scheme is based on coding the ...