Wavelength Selection for NIR Spectroscopy Based on the Binary Dragonfly Algorithm [PDF]
Molecules, 2019 Wavelength selection is an important preprocessing issue in near-infrared (NIR) spectroscopy analysis and modeling. Swarm optimization algorithms (such as genetic algorithm, bat algorithm, etc.) have been successfully applied to select the most effective
Yuanyuan Chen, Zhibin Wang
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Remote 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
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EEG-based epileptic seizure detection using binary dragonfly algorithm and deep neural network [PDF]
Scientific Reports, 2023 Electroencephalogram (EEG) is one of the most common methods used for seizure detection as it records the electrical activity of the brain. Symmetry and asymmetry of EEG signals can be used as indicators of epileptic seizures.
G. Yogarajan +7 more
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Gender-based Alzheimer's detection using ResNet-50 and binary dragonfly algorithm on neuroimaging [PDF]
Frontiers in Artificial IntelligenceAlzheimer's disease (AD) is an incurable, progressive neurodegenerative disorder. It is characterized by a gradual decline in memory, cognition, and behavior, which ultimately results in severe dementia and functional dependence.
Muhammad Ikram ul Haq +9 more
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IBDA: Improved Binary Dragonfly Algorithm With Evolutionary Population Dynamics and Adaptive Crossover for Feature Selection [PDF]
IEEE 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
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Entropy, 2021 The dragonfly algorithm (DA) is a new intelligent algorithm based on the theory of dragonfly foraging and evading predators. DA exhibits excellent performance in solving multimodal continuous functions and engineering problems.
Lin Wang, Ronghua Shi, Jian Dong
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Optimal Planning for the Development of Power System in Respect to Distributed Generations Based on the Binary Dragonfly Algorithm [PDF]
Applied Sciences, 2020 With the increasing number of population and the rising demand for electricity, providing safe and secure energy to consumers is getting more and more important. Adding dispersed products to the distribution network is one of the key factors in achieving
Mohammad Hossein Kakueinejad +3 more
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A HLBDA, GA, and COA for optimal operation of distributed energy resources. [PDF]
PLoS ONEAlthough renewable energy sources offer enormous potential to improve environmental sustainability, maximizing economic benefits inside microgrids requires resolving their intermittency and irregularity.
Bilal Naji Alhasnawi +10 more
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Hybrid feature selection for IoMT based intrusion detection system for integrating mutual information filtering with deep learning based accelerated metaheuristic optimization [PDF]
Scientific ReportsThe rapid development of the Internet of Medical Things (IoMT) has significantly expanded the cybersecurity attack perimeter of healthcare systems (HCS).
Saranya Palaniappan, Sudhakar Sengan
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Hybrid Synthetic Minority Over-sampling Technique (HSMOTE) and Ensemble Deep Dynamic Classifier Model (EDDCM) for big data analytics [PDF]
Scientific ReportsBig Data Classification (BDC) has become increasingly important across domains such as healthcare, e-commerce, and banking. However, challenges such as high dimensionality and class imbalance often degrade the performance of conventional machine learning
Priyadharsini M +3 more
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