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3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm.
Pan, Jeng-Shyang; Chai, Qing-Wei; Chu, Shu-Chuan; Wu, Ning.
Afiliação
  • Pan JS; College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
  • Chai QW; College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
  • Chu SC; College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
  • Wu N; School of Electronic and Information Engineering, Beibu Gulf University, Qinzhou 535011, China.
Sensors (Basel) ; 20(8)2020 Apr 23.
Article em En | MEDLINE | ID: mdl-32340324
ABSTRACT
In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH algorithm is verified by the CEC 2013 test suit, and shows better results than the original BH. In addition, the EBH and other celebrated algorithms can be used to solve node coverage problems of Wireless Sensor Network (WSN) in 3-D terrain with satisfactory performance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article