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High voltage transmission line fault classification based on neural network trained by particle swarm optimization
Published 2017“…The use of neural system way to deal with recognize the fault classification of the transmission lines is led in this review. …”
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Feature selection based on particle swarm optimization algorithm for sentiment analysis classification
Published 2021“…Furthermore, the proposed algorithm solves the complex background problems about noise data and feature selection that affect the classification performance on sentiment analysis. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Then, the selected features are given as input to the DBN classifier which is trained using the Taylor-based bird swarm algorithm (Taylor-BSA). Taylor-BSA is designed by combining the Taylor series and bird swarm algorithm (BSA).…”
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Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation
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Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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A survey : particle swarm optimization-based algorithms for grid computing scheduling systems.
Published 2013“…This study surveys PSObased scheduling algorithms for Grid systems and presents a classification for the various approaches adopted. …”
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Particle swarm optimization for neural network learning enhancement
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On the exploration and exploitation in popular swarm-based metaheuristic algorithms
Published 2018“…This study, therefore, performed in-depth empirical analysis by quantitatively analyzing exploration and exploitation of five swarm-based metaheuristic algorithms. The analysis unearthed explanations the way algorithms performed on numerical problems as well as on real-world application of classification using adaptive neuro-fuzzy inference system (ANFIS) trained by selected metaheuristics. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Malicious URL classification using artificial fish swarm optimization and deep learning
Published 2023“…With this motivation, the current article develops an Artificial Fish Swarm Algorithm (AFSA) with Deep Learning Enabled Malicious URL Detection and Classification (AFSADL-MURLC) model. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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A novel approach to data mining using simplified swarm optimization
Published 2011“…In this thesis, a novel Simplified Swarm Optimization (SSO) algorithm is proposed as a rule-based classifier and for feature selection. …”
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