Diversity enhanced ion motion optimization for localization in wireless sensor network

Jeng Shyang Pan; Trong The Nguyen; Shu Chuan Chu; Thi Kien Dao; Truong Giang Ngo

Diversity enhanced ion motion optimization for localization in wireless sensor network

Jeng Shyang Pan, Trong The Nguyen, Shu Chuan Chu, Thi Kien Dao, Truong Giang Ngo

College of Science and Engineering

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

A new optimization algorithm (named DIMO) based on diversity enhanced Ion Motion Optimization (IMO) is proposed. Diversity learning strategy and random perturbations are applied to improve IMO by modifying its individual evolutionary information. A set of selected benchmark functions and an estimation localization in Wireless sensor network (WSN) are used to test the performance of the proposed algorithm. The experimental results compared with the others algorithms in the literature shows that the proposed approach are superior to the other algorithms in optimization accuracy, convergence speed, and robustness.

Original language	English
Pages (from-to)	221-229
Number of pages	9
Journal	Journal of Information Hiding and Multimedia Signal Processing
Volume	10
Issue number	1
Publication status	Published - Jan 2019

Keywords

DIMO
Meta-heuristic
Wireless sensor network
Global Positioning System
GPS
WSN
Ion Motion
Optimization

Access to Document

http://bit.kuas.edu.tw/~jihmsp/2019/vol1/JIH-MSP-2019-01-24.pdfLicence: In Copyright

Fingerprint Dive into the research topics of 'Diversity enhanced ion motion optimization for localization in wireless sensor network'. Together they form a unique fingerprint.

Cite this

@article{08c2d6a4218b4f67b958cf24880f0d3f,

title = "Diversity enhanced ion motion optimization for localization in wireless sensor network",

abstract = "A new optimization algorithm (named DIMO) based on diversity enhanced Ion Motion Optimization (IMO) is proposed. Diversity learning strategy and random perturbations are applied to improve IMO by modifying its individual evolutionary information. A set of selected benchmark functions and an estimation localization in Wireless sensor network (WSN) are used to test the performance of the proposed algorithm. The experimental results compared with the others algorithms in the literature shows that the proposed approach are superior to the other algorithms in optimization accuracy, convergence speed, and robustness.",

keywords = "DIMO, Meta-heuristic, Wireless sensor network, Global Positioning System, GPS, WSN, Ion Motion, Optimization",

author = "Pan, {Jeng Shyang} and Nguyen, {Trong The} and Chu, {Shu Chuan} and Dao, {Thi Kien} and Ngo, {Truong Giang}",

year = "2019",

month = jan,

language = "English",

volume = "10",

pages = "221--229",

journal = "Journal of Information Hiding and Multimedia Signal Processing",

issn = "2073-4212",

number = "1",

}

TY - JOUR

T1 - Diversity enhanced ion motion optimization for localization in wireless sensor network

AU - Pan, Jeng Shyang

AU - Nguyen, Trong The

AU - Chu, Shu Chuan

AU - Dao, Thi Kien

AU - Ngo, Truong Giang

PY - 2019/1

Y1 - 2019/1

N2 - A new optimization algorithm (named DIMO) based on diversity enhanced Ion Motion Optimization (IMO) is proposed. Diversity learning strategy and random perturbations are applied to improve IMO by modifying its individual evolutionary information. A set of selected benchmark functions and an estimation localization in Wireless sensor network (WSN) are used to test the performance of the proposed algorithm. The experimental results compared with the others algorithms in the literature shows that the proposed approach are superior to the other algorithms in optimization accuracy, convergence speed, and robustness.

AB - A new optimization algorithm (named DIMO) based on diversity enhanced Ion Motion Optimization (IMO) is proposed. Diversity learning strategy and random perturbations are applied to improve IMO by modifying its individual evolutionary information. A set of selected benchmark functions and an estimation localization in Wireless sensor network (WSN) are used to test the performance of the proposed algorithm. The experimental results compared with the others algorithms in the literature shows that the proposed approach are superior to the other algorithms in optimization accuracy, convergence speed, and robustness.

KW - DIMO

KW - Meta-heuristic

KW - Wireless sensor network

KW - Global Positioning System

KW - GPS

KW - WSN

KW - Ion Motion

KW - Optimization

UR - http://www.scopus.com/inward/record.url?scp=85059371579&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:85059371579

VL - 10

SP - 221

EP - 229

JO - Journal of Information Hiding and Multimedia Signal Processing

JF - Journal of Information Hiding and Multimedia Signal Processing

SN - 2073-4212

IS - 1

ER -