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- W2574637900 abstract "As in the competitive environment, it becomes necessary to focus on retaining churn customers as well as attracting new customers. Various algorithms of Data Mining have been used for making distinguish between customers into loyal and churn. This paper represents the ant bee colony algorithm which has been used to get accurate results. The use of ABC with two best values local best and global best makes it more effective to obtain the more pleasing and comfortable results. PSO is used to search the best solution with two best values named pbst and gbst by using iteration with initial velocity and positions." @default.
- W2574637900 created "2017-01-26" @default.
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- W2574637900 date "2017-01-17" @default.
- W2574637900 modified "2023-09-23" @default.
- W2574637900 title "Evaluating Prediction of Customer Churn Behavior Based On Artificial Bee Colony Algorithm" @default.
- W2574637900 cites W2003271439 @default.
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- W2574637900 doi "https://doi.org/10.18535/ijecs/v6i1.32" @default.
- W2574637900 hasPublicationYear "2017" @default.
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