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An improved Dragonfly Algorithm for feature selection
Knowledge-Based Systems, 2020Abstract Dragonfly Algorithm (DA) is a recent swarm-based optimization method that imitates the hunting and migration mechanisms of idealized dragonflies. Recently, a binary DA (BDA) has been proposed. During the algorithm iterative process, the BDA updates its five main coefficients using random values.
Majdi Mafarja +2 more
exaly +3 more sources
Chaotic dragonfly algorithm: an improved metaheuristic algorithm for feature selection
Applied Intelligence, 2018Selecting the most discriminative features is a challenging problem in many applications. Bio-inspired optimization algorithms have been widely applied to solve many optimization problems including the feature selection problem. In this paper, the most discriminating features were selected by a new Chaotic Dragonfly Algorithm (CDA) where chaotic maps ...
Gehad Ismail Sayed +2 more
exaly +3 more sources
Connectivity and constructive algorithms of disjoint paths in dragonfly networks
Theoretical Computer Science, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Suying Wu +4 more
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Wind driven dragonfly algorithm for global optimization
Concurrency and Computation: Practice and Experience, 2020SummaryDragonfly algorithm (DA) is a new swarm intelligence optimization algorithm based on the static and dynamic swarm behavior of dragonflies. The algorithm has the characteristics of simple structure, strong search ability, easy implementation, and strong robustness.
Lianlian Zhong +3 more
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A New Set of Mutation Operators for Dragonfly Algorithm
Arabian Journal for Science and Engineering, 2021Dragonfly algorithm (DA) is a recently introduced, swarm intelligent algorithm and has proved its worth over real-world optimization problems. The algorithm is very efficient but is computationally expensive, has poor exploration properties, and unbalanced cohesion and alignment operation. In the present work, the concept of mutation operators has been
Rohit Salgotra +4 more
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2017
The dragonfly algorithm (DA) is a new metaheuristic optimization algorithm, which is based on simulating the swarming behavior of dragonfly individuals. This algorithm was developed by Mirjalili (2016) and the preliminary studies illustrated its potential in solving numerous benchmark optimization problems and complex computational fluid dynamics (CFD)
Babak Zolghadr-Asli +2 more
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The dragonfly algorithm (DA) is a new metaheuristic optimization algorithm, which is based on simulating the swarming behavior of dragonfly individuals. This algorithm was developed by Mirjalili (2016) and the preliminary studies illustrated its potential in solving numerous benchmark optimization problems and complex computational fluid dynamics (CFD)
Babak Zolghadr-Asli +2 more
openaire +3 more sources
Memory based Hybrid Dragonfly Algorithm for numerical optimization problems
Expert Systems With Applications, 2017A novel hybrid algorithm (MHDA) based on Dragon Fly and PSO is proposed.Performance is tested using standard benchmark problems.Proposed algorithm is compared with well-known optimization algorithms.Statistical analysis is done using Friedmans test and Wilcoxon signed ranksum test.Superiority of MHDA is also proved by applying on engineering design ...
Murugan S., Sree Ranjini K S
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Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm
Journal of Cleaner Production, 2020 [[abstract]]It is hard to predict wind power with high-precision due to its non-stationary and stochastic nature. The wind power has developed rapidly around the world as a promising renewable energy industry.
Ming-Lang Tseng, Raymond Tan
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A Spark-based Distributed Dragonfly Algorithm for Feature Selection
2020 15th International Conference on Computer Science & Education (ICCSE), 2020Dragonfly algorithm is an intelligent group optimization algorithm. In this paper, dragonfly algorithm is well used in the field of feature selection. However, dragonfly algorithm has the problem of falling into local optimal solution, which reduces the performance of feature selection and classification.
Hongwei Chen +5 more
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A hybrid dragonfly algorithm with extreme learning machine for prediction
2016 International Symposium on INnovations in Intelligent SysTems and Applications (INISTA), 2016In this work, a proposed hybrid dragonfly algorithm (DA) with extreme learning machine (ELM) system for prediction problem is presented. ELM model is considered a promising method for data regression and classification problems. It has fast training advantage, but it always requires a huge number of nodes in the hidden layer.
Mustafa Abdul Salam +4 more
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