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103962

A New Multi-layer Perceptron Trainer based on Dragonfly Optimization Algorithm.

Article

Last updated: 22 Jan 2023

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Tags

Electrical Engineering

Abstract

In this paper, Dragonfly Optimizer (DO) was used to train Multi-Layer Perceptron (MLP). DO was used to find the weights and biases of the MLP to achieve a minimum error and a high classification accuracy. Four standard classification datasets were used to benchmark the performance of the proposed method. In addition, the performance of the proposed method were compared with three well-known optimization algorithms, namely, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Grey Wolf Optimizer (GWO) which were used to train MLP also. The experimental results showed that the DO algorithm with the MLP was very competitive as it solved the local optima problem and achieved high accuracy

DOI

10.21608/bfemu.2020.103962

Keywords

Dragonfly Optimizer, Neural Network and Multi-Layer Perceptron

Authors

First Name

Mohy Eldin

Last Name

Abo-Elsoud

MiddleName

A.

Affiliation

Prof.,Communication department., Faculty of Eng., Mansoura University

Email

-

City

-

Orcid

-

First Name

Mohamed

Last Name

Morsy

MiddleName

-

Affiliation

Doctor.,Communication department., Faculty of Eng., Mansoura University.

Email

-

City

-

Orcid

-

First Name

Shaima

Last Name

Elnazer

MiddleName

-

Affiliation

, lecture assistant at Nile academy, Mansoura University

Email

shima_elnazer@yahoo.com

City

-

Orcid

-

Volume

41

Article Issue

4

Related Issue

15137

Issue Date

2016-12-01

Receive Date

2016-05-11

Publish Date

2016-12-01

Page Start

11

Page End

19

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 41_Issue 4_Pages 11-19.pdf

PDF . 934.5kB

Link

https://bfemu.journals.ekb.eg/article_103962.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=103962

Order

6

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023