Hybrid Genetic Algorithm with K-Means for Clustering Problems
نویسندگان
چکیده
منابع مشابه
Hybrid Genetic Algorithm with K-Means for Clustering Problems
The K-means method is one of the most widely used clustering methods and has been implemented in many fields of science and technology. One of the major problems of the k-means algorithm is that it may produce empty clusters depending on initial center vectors. Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary principles of natural selection and genetics...
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GA-based clustering algorithms often employ either simple GA, steady state GA or their variants and fail to consistently and efficiently identify high quality solutions (best known optima) of given clustering problems, which involve large data sets with many local optima. To circumvent this problem, we propose Niching Genetic K-means Algorithm (NGKA) that is based on modified deterministic crow...
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ژورنال
عنوان ژورنال: Open Journal of Optimization
سال: 2016
ISSN: 2325-7105,2325-7091
DOI: 10.4236/ojop.2016.52009