Title: A Modified Genetic Algorithm Initializing K-Means Clustering
Abstract:s In this paper, a new clustering algorithm is proposed called Modified Genetic Algorithm Initializing KM (MGAIK). MGAIK is inspired by the Genetic Algorithm as an initialization method for K-means cl...s In this paper, a new clustering algorithm is proposed called Modified Genetic Algorithm Initializing KM (MGAIK). MGAIK is inspired by the Genetic Algorithm as an initialization method for K-means clustering but features several improvement over GAIK. The experiment indicates that, while K-Means algorithm converges to local minima and in its initialization step where it is normally done randomly, both MGAIK and GAIK always converge to global optimum eventually but MGAIK, a natural way to speed up GA processes is to evaluate the individuals in parallel rather than sequentially.Simple genetic algorithm (GA) involves only one initial population with fixed genetic operational parameters selected in advance. This paper presents a modified genetic algorithm (MGA) with multiple subpopulations and dynamic parameters. To show the effectiveness and efficiency of the algorithms, a comparative study was done among K-means,Read More
Publication Year: 2011
Publication Date: 2011-02-03
Language: en
Type: article
Access and Citation
Cited By Count: 11
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot