Search Results - (( stone detection method algorithm ) OR ( swarm classification system algorithm ))*

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  1. 1
    Using a novel algorithm in ultrasound images to detect renal stones

    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…Expectation–Maximization algorithm is a novel method used by us for the first time for identifying renal stones. …”
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  2. 2
    High voltage transmission line fault classification based on neural network trained by particle swarm optimization

    High voltage transmission line fault classification based on neural network trained by particle swarm optimization by Zukri, Muhamad Amirul Aizad

    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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  3. 3
    Feature selection based on particle swarm optimization algorithm for sentiment analysis classification

    Feature selection based on particle swarm optimization algorithm for sentiment analysis classification by Nurcahyawati, Vivine, Mustaffa, Zuriani

    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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  4. 4
    The optimization of stepping stone detection: packet capturing steps

    The optimization of stepping stone detection: packet capturing steps by Omar, Mohd. Nizam, Maarof, Mond. Aizaini, Zainal, Anazida

    Published 2006
    “…This paper proposes an optimized packet capturing stone detection algorithm that can shorten the response time of overall response mechanism. …”
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  5. 5
    Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification

    Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification by Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    Published 2022
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  6. 6
    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    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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  7. 7
    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation

    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

    Published 2011
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  8. 8
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    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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  9. 9
    The optimization of stepping stone detection : packet capturing steps

    The optimization of stepping stone detection : packet capturing steps by Omar, Mohd. Nizam, Maarof, Mohd. Aizaini, Zainal, Anazida

    Published 2006
    “…This paper proposes an optimized packet capturing stone detection algorithm that can shorten the response time of overall response mechanism. …”
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  10. 10
    The optimization of stepping stone detection: Packet capturing steps

    The optimization of stepping stone detection: Packet capturing steps by Omar, Mohd Nizam, Maarof, Mohd Aizaini, Zainal, Anazida

    Published 2006
    “…This paper proposes an optimized packet capturing stone detection algorithm that can shorten the response time of overall response mechanism.The aim of the research is to improve the packet capturing step in stepping stone algorithm, thus, improve the response from overall detection and response system.The proposed method is to use small size of user buffer and kernel buffer.Experiments were conducted with two types of packet stream; i) 10 kbps and ii) 10 000 kbps data generated by Tfgen (packet generator) tools and nine combinations of different buffer sizes for each network packet stream were tested.Results from the experiment were analyzed. …”
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  11. 11
    An improved data classification framework based on fractional particle swarm optimization

    An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

    Published 2019
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  12. 12
    A survey : particle swarm optimization-based algorithms for grid computing scheduling systems.

    A survey : particle swarm optimization-based algorithms for grid computing scheduling systems. by Ambursa, Faruku Umar, Latip, Rohaya

    Published 2013
    “…This study surveys PSObased scheduling algorithms for Grid systems and presents a classification for the various approaches adopted. …”
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  13. 13
    Particle swarm optimization for neural network learning enhancement

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
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  14. 14
    On the exploration and exploitation in popular swarm-based metaheuristic algorithms

    On the exploration and exploitation in popular swarm-based metaheuristic algorithms by Hussain, Kashif, Mohd Salleh, Mohd Najib, Cheng, Shi, Shi, Yuhui

    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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  15. 15
    A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System

    A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System by Al Ghuraibawi, Adnan Hasan Bdair

    Published 2023
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  16. 16
    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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  17. 17
    Improving ant swarm optimization with embedded vaccination for optimum reducts generation

    Improving ant swarm optimization with embedded vaccination for optimum reducts generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

    Published 2013
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  18. 18
    Malicious URL classification using artificial fish swarm optimization and deep learning

    Malicious URL classification using artificial fish swarm optimization and deep learning by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, K. Nour, Mohamed, M. Asiri, Mashael, M. Al-Sharafi, Ali, Othman, Mahmoud, Motwakel, Abdelwahed

    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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  19. 19
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    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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  20. 20
    Using the bees algorithm to optimise a support vector machine for wood defect classification

    Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

    Published 2007
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