Results 21 to 30 of about 8,403 (210)

Binary Dragonfly Algorithm for Feature Selection [PDF]

open access: yes2017 International Conference on New Trends in Computing Sciences (ICTCS), 2017
Wrapper feature selection methods aim to reduce the number of features from the original feature set to and improve the classification accuracy simultaneously. In this paper, a wrapper-feature selection algorithm based on the binary dragonfly algorithm is proposed. Dragonfly algorithm is a recent swarm intelligence algorithm that mimics the behavior of
Majdi M. Mafarja   +4 more
openaire   +1 more source

A Hybrid Binary Dragonfly Algorithm with an Adaptive Directed Differential Operator for Feature Selection

open access: yesRemote Sensing, 2023
Feature selection is a typical multiobjective problem including two conflicting objectives. In classification, feature selection aims to improve or maintain classification accuracy while reducing the number of selected features. In practical applications,
Yilin Chen   +6 more
doaj   +1 more source

Dragonfly-Based Joint Delay/Energy LTE Downlink Scheduling Algorithm

open access: yesIEEE Access, 2020
Managing radio resources in Long Term Evolution (LTE) networks is considered as one of the essential design factors for enhancing the overall system performance.
Heba Nashaat   +3 more
doaj   +1 more source

Dragonfly algorithm in 2020: review

open access: yesCommunications in Mathematical Biology and Neuroscience, 2021
Swarm Intelligence is the meta-heuristic algorithm that is inspired by the natural behavior of some groups of animals (like dragonfly, ants, ducks, etc.) striving for their life existence. One of them is Dragonfly Algorithm. Dragonfly Algorithm has been used to solve real-world nonlinear problems in engineering.
openaire   +1 more source

A Survey on Dragonfly Algorithm and its Applications in Engineering [PDF]

open access: yesEvolutionary Intelligence, 2021
<p></p><p></p><p>The dragonfly algorithm developed in 2016. It is one of the algorithms used by the researchers to optimize an extensive series of uses and applications in various areas. At times, it offers superior performance compared to the most well-known optimization techniques.
Chnoor M. Rahman   +5 more
openaire   +5 more sources

Apple classification based on multi-information fusion and DA-DBN

open access: yesShipin yu jixie, 2023
Objective: In order to improve the precision of apple grade judgment model, the method of apple grade judgment was established. Methods: A decision model of apple rank based on multi-information fusion and dragonfly algorithm was proposed.
CHEN Haixia, JIA Zhijuan, ZHAO Yunping
doaj   +1 more source

Positioning algorithm based on improved dragonfly optimization

open access: yesInternational Journal of Computer Science and Information Technology, 2023
Aiming at solving the nonlinear equation of indoor arrival time difference positioning, a multi-strategy improved dragonfly optimization algorithm is proposed. The initial population is improved by chaotic mapping, and then nonlinear factors and Cauchy mutation operators are introduced to rapidly converge the balanced global search and local search. At
Yue Zhang, Hongping Pu, Wei Chen
openaire   +1 more source

Optimasi Ekonomi dan Emisi Pembangkit Listrik di Kalimantan menggunakan Dragonfly Algoritmh

open access: yesJurnal Elkomika, 2021
ABSTRAK Kebutuhan listrik di Kalimantan Selatan dan Tengah menjadi semakin bertambah dikarenakan meningkatnya jumlah penduduk dan ekonomi serta mahalnya biaya pembangkitan listrik.
BAYU SETYO WIBOWO   +2 more
doaj   +1 more source

Measuring and Understanding Throughput of Network Topologies [PDF]

open access: yes, 2016
High throughput is of particular interest in data center and HPC networks. Although myriad network topologies have been proposed, a broad head-to-head comparison across topologies and across traffic patterns is absent, and the right way to compare worst ...
Godfrey, P. Brighten   +3 more
core   +1 more source

IBDA: Improved Binary Dragonfly Algorithm With Evolutionary Population Dynamics and Adaptive Crossover for Feature Selection

open access: yesIEEE Access, 2020
Feature selection is an effective method to eliminate irrelevant, redundant and noisy features, which improves the performance of classification and reduces the computational burden in machine learning.
Jiahui Li   +6 more
doaj   +1 more source

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