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DBSCAN-Based Adaptive Bacterial Foraging Algorithm(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2014年03期
Page:
63-
Research Field:
Publishing date:

Info

Title:
DBSCAN-Based Adaptive Bacterial Foraging Algorithm
Author(s):
Wang Yang; Xie Fen; Liu Qing
School of Computer Science and Technology,Nanjing Normal University,Nanjing 210023,China
Keywords:
BFA; adaptive chemotactic step size; algorithm premature; DBSAN
PACS:
TP18
DOI:
-
Abstract:
The adaptive bacterial foraging algorithm(ABFA),to some extent,solves the problem of chemotactic step size choice in bacterial foraging algorithm(BFA)and subsequently accelerates the convergence rate.However,along with the decrease of bacterial cost function value,the original chemotactic step size adjust function is liable to make chemotactic step size minimum,leading to the algorithm premature.Adaptive bacterial foraging algorithm based on density-based spatial clustering of applications with noise(DBSCAN-based adaptive bacterial foraging algorithm,DBSCAN-ABFA)is designed,with the purpose of avoiding the algorithm premature by changing the chemotactic step size adjust function of the labeled core points bacterial according to DBSCAN,and the improved chemotactic step size adjust function can reduce the shrink rate of step size,so the algorithm premature is ultimately avoided.To verify the feasibility of the algorithm,trials are also designed.

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Last Update: 2014-09-30